TCC
Leonardo Fernandes Wink
04/10/2022
1 Brief explanation
Every boxplot means a monitoring point (Ponto de monitoramento (or PM) in portuguese). My goal here is to analyze the evolution between decades of each water quality parameter that compounds the Water Quality Index (WQI).
The river flows in the east-west direction as shown in the image below.
The logic behind the sorting in the boxplots is because of 2 main reasons:
- The original monitoring point isn’t easy to understand (8 digits, like 87409900)
- Changing the original nomenclature to PM1, PM2 (…) makes it easier to understand that the last point has water contributions of every other point upstream.
Some features that I want to add: - If the parameter is x, then use x’s classes (with its own classes background color plotted) - Define the timescale, should act just like a filter
# plan_wide_19902020 %>%
# filter(ANO_COLETA > "1990" &
# ANO_COLETA <= "2000")2 Anotações de coisas por fazer:
- Descobrir como colocar as estações no sentido correto montante -> jusante nos sumários
87398500, 87398980, 87398900, 87398950, 87405500, 87406900, 87409900
Aprender a segmentar o meu dataset por períodos- aprender a criar uma nova coluna com a segmentação dos períodos
- maybe use
~facet.grid - aprender a colocar a legenda dentro do gráfico
- reduzir o tamanho da legenda
corrigir os valores 0 de IQA pra NA- descobrir como conseguir a equação do lm
aprender a pivotar o sumário-> meu sumário do google docs ta batendo direitinho com o do R- descobrir se há outros TCCs com disponibilização de códigos
Namontá com com casa decimal","eptottá com"."- correlação forte entre condutividade e Namon/Ptot/DBO
| 1990-2000 | 2000-2010 | 2010-2020 |
|---|---|---|
| 1990-2000 | 2000-2010 | 2010-2020 |
3 Instalar os pacotes
# install.packages(tidyverse)3.1 acessar os pacotes
# library(readr)
# library(rmarkdown)
# # library(qboxplot)
# library(readxl)
# library(pillar)
# library(dplyr)
# library(tidyverse)
# library(gapminder)
# library(knitr)
# library(kableExtra)
# library(ggpubr)
# library(gridExtra)
# library(modelsummary)
# library(gtsummary)
# library(GGally)
pacman::p_load(readr, rmarkdown, readxl,
pillar, dplyr, tidyverse,
gapminder, knitr, kableExtra,
gridExtra, #modelsummary,
gtsummary, ggplot2,
ggbeeswarm, GGally)
# pacman::p_load(tibbletime)knitr::knit_hooks$set(time_it = local({
now <- NULL
function(before, options) {
if (before) {
# record the current time before each chunk
now <<- Sys.time()
} else {
# calculate the time difference after a chunk
res <- difftime(Sys.time(), now)
# return a character string to show the time
paste("Time for this code chunk to run:", res)
}
}
}))
knitr::opts_chunk$set(time_it = TRUE)3.2 importando a planilha
## Rows: 1,179
## Columns: 53
## $ CODIGO <chr> "87398950", "87398900", "87405500", "87398950", "8~
## $ MUNICIPIO <chr> "GRAVATAI - RS", "GRAVATAI - RS", "CACHOEIRINHA - ~
## $ ENDERECO <chr> "A PE NO TREVO, NA PONTE VELHA OU DE BARCO VINDO D~
## $ COORD_GEO_LAT_GRAU <dbl> -51.00064, -50.93414, -51.11733, -51.00064, -50.93~
## $ COORD_GEO_LONG_GRAU <dbl> -29.95055, -29.95075, -29.95055, -29.95055, -29.95~
## $ Altitude <dbl> 7, 6, 6, 7, 6, 7, 9, 9, 6, 6, 6, 6, 7, 6, 7, 6, 13~
## $ RECURSO_HIDRICO <chr> "RIO GRAVATAI", "RIO GRAVATAI", "RIO GRAVATAI", "R~
## $ DATA_COLETA <date> 1994-12-08, 1994-02-03, 1994-02-03, 1993-10-06, 1~
## $ ANO_COLETA <dbl> 1994, 1994, 1994, 1993, 1994, 1995, 1994, 1995, 19~
## $ Alcalinidade <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ Condutividade <dbl> 90.0, 47.0, 147.0, 43.0, NA, 47.0, 70.0, 60.6, 72.~
## $ DBO <dbl> 5, 5, 11, 3, 3, 2, 4, 3, 4, 2, 5, 3, 1, 1, 5, 2, 2~
## $ IQA_DBO <dbl> 53.97, 53.97, 29.03, 69.06, 69.06, 78.12, 61.05, 6~
## $ DQO <dbl> 26, 47, 34, 37, 54, 23, 35, 25, 28, 40, 21, 35, 21~
## $ E_coli <dbl> 4.0, 40.0, 12.8, 10.4, 32.0, 16.8, 40.0, 6.4, 10.4~
## $ fosfato_orto <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ fosforo_total <dbl> 0.1130, 0.0883, 0.3530, 0.0908, 0.1180, 0.0326, 0.~
## $ IQA_Ptot <dbl> 72.73, 77.95, 38.26, 77.41, 71.71, 91.16, 63.37, 6~
## $ Nitrato <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ Nitrito <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ nitro_organico <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ nitro_amon <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ nitro_kjeldahl <dbl> 1.42, 1.61, 6.62, 0.79, 1.45, 0.76, 1.23, 1.37, 2.~
## $ nitro_total <dbl> 1.42, 1.61, 6.62, 0.79, 1.45, 0.76, 1.23, 1.37, 2.~
## $ IQA_NitroTot <dbl> 89.02, 87.64, 59.33, 93.74, 88.80, 93.97, 90.41, 8~
## $ oxigenio_dissolvido <dbl> 6.5, 8.7, 5.3, 7.8, 7.6, 8.5, 7.3, 6.9, 6.7, 6.3, ~
## $ sat_OD <dbl> 78.162, 116.280, 70.837, 85.270, 96.442, 85.565, 7~
## $ IQA_OD <dbl> 84.58, 90.92, 76.25, 89.67, 97.53, 89.88, 79.57, 7~
## $ pH <dbl> 6.9, 6.8, 6.6, 6.4, 6.9, 6.7, 6.6, 6.7, 6.3, 7.1, ~
## $ IQA_pH <dbl> 89.76, 87.72, 82.86, 76.96, 89.76, 85.42, 82.86, 8~
## $ SDT <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ SST <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ temp_agua <dbl> 25.0, 31.0, 31.0, 20.0, 28.0, 16.0, 16.0, 16.0, 18~
## $ temp_ar <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ transparencia_agua <dbl> NA, 40.0, 30.0, NA, NA, NA, 50.0, 20.0, 40.0, 20.0~
## $ turbidez <dbl> 20.0, 20.0, 8.5, 23.0, 19.0, 17.0, 12.0, 22.0, 17.~
## $ IQA_Turb <dbl> 61.87, 61.87, 80.20, 58.73, 63.07, 65.69, 73.57, 5~
## $ vazao_rio <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ Vazao <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ coliformes_termo <dbl> 5, 50, 16, 13, 40, 21, 50, 8, 13, 23, 700, 16, 8, ~
## $ IQA_coli <dbl> 76.58, 47.21, 60.44, 63.04, 49.66, 57.12, 47.21, 6~
## $ solidos_totais <dbl> 121, 112, 160, 93, 127, 75, 80, 201, 84, 123, 78, ~
## $ IQA_Sól_Tot <dbl> 83.91, 84.69, 79.40, 85.78, 83.28, 86.08, 86.07, 7~
## $ `IQA_^OD` <dbl> 2.126, 2.153, 2.089, 2.148, 2.178, 2.148, 2.104, 2~
## $ `IQA_^temp_agua` <dbl> 1.58, 1.58, 1.58, 1.58, 1.58, 1.58, 1.58, 1.58, 1.~
## $ `IQA_^coli` <dbl> 1.917, 1.783, 1.850, 1.862, 1.796, 1.835, 1.783, 1~
## $ `IQA_^pH` <dbl> 1.715, 1.711, 1.699, 1.684, 1.715, 1.705, 1.699, 1~
## $ `IQA_^DBO` <dbl> 1.175, 1.175, 1.271, 1.116, 1.116, 1.072, 1.149, 1~
## $ `IQA_^NitroTot` <dbl> 1.567, 1.564, 1.504, 1.575, 1.566, 1.575, 1.569, 1~
## $ `IQA_^Ptot` <dbl> 1.535, 1.546, 1.440, 1.545, 1.533, 1.570, 1.514, 1~
## $ `IQA_^Turb` <dbl> 1.391, 1.391, 1.420, 1.385, 1.393, 1.398, 1.410, 1~
## $ `IQA_^Sól_Tot` <dbl> 1.425, 1.426, 1.419, 1.428, 1.424, 1.428, 1.428, 1~
## $ IQA <dbl> 61.876, 58.452, 57.556, 57.129, 56.405, 56.189, 55~Time for this code chunk to run: 1.96366381645203
Time for this code chunk to run: 0.219733953475952
4 data wrangling
# Como há dados faltantes, no cálculo entre o produto das colunas, ele acaba interpretando como se fosse zero, mas na verdade é NA
plan_wide_19902020 <- plan_wide_19902020 %>%
mutate(IQA = ifelse(IQA == 0, NA, IQA))
parametros_IQA <- plan_wide_19902020 %>%
select(CODIGO,
pH,
DBO,
E_coli,
nitro_amon,
nitro_kjeldahl,
nitro_total,
fosforo_total,
temp_agua,
turbidez,
solidos_totais,
oxigenio_dissolvido,
Condutividade)
write.csv(parametros_IQA,
"./parametros_IQA.csv",
row.names = FALSE)
plan_wide_19902020 %>%
select(starts_with("IQA_^")) %>%
mutate(
TESTANDOIQA = prod()
)## # A tibble: 1,179 x 10
## `IQA_^OD` IQA_^temp~1 IQA_^~2 IQA_^~3 IQA_^~4 IQA_^~5 IQA_^~6 IQA_^~7 IQA_^~8
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2.13 1.58 1.92 1.72 1.18 1.57 1.54 1.39 1.42
## 2 2.15 1.58 1.78 1.71 1.18 1.56 1.55 1.39 1.43
## 3 2.09 1.58 1.85 1.70 1.27 1.50 1.44 1.42 1.42
## 4 2.15 1.58 1.86 1.68 1.12 1.58 1.54 1.38 1.43
## 5 2.18 1.58 1.80 1.72 1.12 1.57 1.53 1.39 1.42
## 6 2.15 1.58 1.84 1.70 1.07 1.58 1.57 1.40 1.43
## 7 2.10 1.58 1.78 1.70 1.15 1.57 1.51 1.41 1.43
## 8 2.08 1.58 1.89 1.70 1.12 1.57 1.52 1.39 1.41
## 9 2.09 1.58 1.86 1.68 1.15 1.56 1.49 1.40 1.43
## 10 2.13 1.58 1.83 1.72 1.07 1.57 1.55 1.38 1.42
## # ... with 1,169 more rows, 1 more variable: TESTANDOIQA <dbl>, and abbreviated
## # variable names 1: `IQA_^temp_agua`, 2: `IQA_^coli`, 3: `IQA_^pH`,
## # 4: `IQA_^DBO`, 5: `IQA_^NitroTot`, 6: `IQA_^Ptot`, 7: `IQA_^Turb`,
## # 8: `IQA_^Sól_Tot`
## # i Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names# library(performance)
# modelo <- plan_wide_19902020 %>%
# select(CODIGO, oxigenio_dissolvido, periodo) %>%
# group_by(CODIGO, periodo) %>%
# lm() %>%
# performance::check_distribution()
# # lm()
#
# check_model(modelo)
# performance::check_autocorrelation(modelo)Time for this code chunk to run: 0.149003982543945
Time for this code chunk to run: 0.00200796127319336
Time for this code chunk to run: 0.00301003456115723
5 setting theme
theme_grafs <- function(bg = "white",
coloracao_letra = "black") {
theme(
plot.title =
element_text(
hjust = 0.5,
color = coloracao_letra,
size = 19),
axis.title.x =
# element_text(
# color = coloracao_letra,
# size = 15,
# angle = 0,),
element_blank(),
axis.title.y = element_text(
color = coloracao_letra,
size = 15,
angle = 90),
axis.text.x = element_text(
color = coloracao_letra,
size = 17),
axis.text.y = element_text(
color = coloracao_letra,
size = 17,
angle = 0),
strip.background = element_rect(fill = bg,
linetype = 1,
size = 0.5,
color = "black"),
strip.text = element_text(size = 17),
panel.background = element_rect(fill = bg),
plot.background = element_rect(fill = bg),
plot.margin = margin(l = 5, r = 10,
b = 5, t = 5)
)
}Time for this code chunk to run: 0.00501489639282227
6 setting different timescales
Time for this code chunk to run: 0.00702309608459473
7 setting sumaries
Time for this code chunk to run: 0.00602006912231445
8 Parâmetros físico-químicos
8.0.1 Oxigênio Dissolvido
Time for this code
chunk to run: 2.07363986968994
Time for this code
chunk to run: 0.606352090835571
Time
for this code chunk to run: 0.609539031982422
Time
for this code chunk to run: 0.510053157806396
grid.arrange(od_p1, od_p2, od_p3, ncol = 3)
Time for this code
chunk to run: 2.11287379264832
ggsave("od.png",
units = c("px"),
width = 4500,
height = 2993,
plot = od,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_p1.png",
plot = od_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_p2.png",
plot = od_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_p3.png",
plot = od_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(od_p1, od_p2, od_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time for
this code chunk to run: 10.2750070095062
Time for this code chunk to run: 0.00702095031738281
Time
for this code chunk to run: 1.05146503448486
Time
for this code chunk to run: 0.902379035949707
Time
for this code chunk to run: 0.720722913742065
grid.arrange(iqaod_p1, iqaod_p2, iqaod_p3, ncol = 3)
Time
for this code chunk to run: 2.26876306533813
## # A tibble: 7 x 8
## par `87398500` `87398900` `87398950` `87398980` `87405500` 874069~1 87409~2
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 min 0.8 2 2.5 4.2 0.1 0.1 0.1
## 2 q1 4.9 5.6 4.4 6 1.9 0.25 1.4
## 3 median 6.4 6.9 5.95 6.3 4.2 2.6 2.9
## 4 mean 5.99 6.78 5.98 7.01 4.22 2.98 3.60
## 5 q3 7.3 8 7.1 8.2 6 5 5.65
## 6 max 10.8 10.5 10.3 12.1 19.9 10.2 11.1
## 7 n 101 101 68 30 97 32 65
## # ... with abbreviated variable names 1: `87406900`, 2: `87409900`## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.4 3.5 4.9 5.01 6.65 10.9
## 2 87398900 1.9 4 5.5 5.33 6.6 12
## 3 87398950 1.7 3.2 5.3 5.06 6.18 8.9
## 4 87398980 1.2 3.8 5.6 5.38 6.6 9.2
## 5 87405500 0.2 1.4 2.55 3.28 4 14.2
## 6 87406900 0 1.1 1.9 2.59 3.15 16
## 7 87409900 0 0.7 2.3 3.12 3.7 10.6## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.38 3.11 4.41 4.57 6.2 12.4
## 2 87398900 3.52 5.25 5.96 6.61 7.3 13.8
## 3 87398950 1.62 3.68 4.92 5.28 6.64 11.9
## 4 87398980 3.37 5.5 6.17 6.48 7.14 13.1
## 5 87405500 0.2 1.3 2.53 2.83 3.66 9.8
## 6 87406900 0.1 0.865 2.4 2.43 3.05 9.1
## 7 87409900 0.1 0.92 2.03 2.43 3.5 8.1Time for this code chunk to run: 0.269903898239136
8.0.2 Demanda Bioquímica de Oxigênio
(dbo <- ggplot(plan_wide_19902020,
aes(x = CODIGO,
y = DBO))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=10,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=5,
ymax=10,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3,
ymax=5,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Demanda Bioquímica de Oxigênio no período 1990-2020",
x="Estação",
y="mg/L")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(1,100),
trans = "log10")+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)## Warning: Transformation introduced infinite values in continuous y-axis## Warning: Removed 60 rows containing non-finite values (stat_boxplot).
## Removed 60 rows containing non-finite values (stat_boxplot).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 22 rows containing missing values (position_quasirandom).## Warning: Removed 30 rows containing missing values (position_quasirandom).## Warning: Removed 8 rows containing missing values (position_quasirandom).
Time for
this code chunk to run: 1.49273705482483
Time
for this code chunk to run: 1.03429794311523
Time
for this code chunk to run: 0.59226393699646
Time
for this code chunk to run: 0.530275106430054
Time
for this code chunk to run: 0.665538787841797
Time
for this code chunk to run: 0.672283172607422
Time
for this code chunk to run: 0.520081043243408
grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3)
Time
for this code chunk to run: 1.60408902168274
(sum_dbo_p1 <- plan_wide_19902020 %>%
select(CODIGO, DBO, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(DBO,
na.rm = TRUE),
q1 =
quantile(DBO, 0.25,
na.rm = TRUE),
median =
median(DBO,
na.rm = TRUE),
mean =
mean(DBO,
na.rm= TRUE),
q3 =
quantile(DBO, 0.75,
na.rm = TRUE),
max =
max(DBO,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 1 1 2 1.86 2 13
## 2 87398900 1 1 1 1.52 2 6
## 3 87398950 1 1 1 1.66 2 6
## 4 87398980 1 1 1 1.13 1 2
## 5 87405500 1 2 3 5.37 5 64
## 6 87406900 1 4 5 9 11 26
## 7 87409900 2 3 4 6.97 9.5 31(sum_dbo_p2 <- plan_wide_19902020 %>%
select(CODIGO, DBO, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(DBO,
na.rm = TRUE),
q1 =
quantile(DBO, 0.25,
na.rm = TRUE),
median =
median(DBO,
na.rm = TRUE),
mean =
mean(DBO,
na.rm= TRUE),
q3 =
quantile(DBO, 0.75,
na.rm = TRUE),
max =
max(DBO,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 1 1 1 1.58 2 5
## 2 87398900 1 1 1 1.40 2 5
## 3 87398950 1 1 1 1.66 2 5
## 4 87398980 1 1 1 1.30 1 5
## 5 87405500 1 2 4 4.67 6.5 14
## 6 87406900 1 3 5 6.53 8 28
## 7 87409900 1 3 6 6.31 9 15(sum_dbo_p3 <- plan_wide_19902020 %>%
select(CODIGO, DBO, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(DBO,
na.rm = TRUE),
q1 =
quantile(DBO, 0.25,
na.rm = TRUE),
median =
median(DBO,
na.rm = TRUE),
mean =
mean(DBO,
na.rm= TRUE),
q3 =
quantile(DBO, 0.75,
na.rm = TRUE),
max =
max(DBO,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 1 1 1.5 2.15 3 7
## 2 87398900 1 1 1 1.51 2 5
## 3 87398950 1 1 2 2.65 2 18
## 4 87398980 1 1 1 1.32 2 2
## 5 87405500 1 3 4 5.28 6.25 21
## 6 87406900 1 3 5 6.58 10 24
## 7 87409900 1 3 4.5 6.18 8 18Time for this code chunk to run: 0.162039995193481
ggsave("dbo.png",
units = c("px"),
width = 4500,
height = 2993,
plot = dbo,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_p1.png",
plot = dbo_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_p2.png",
plot = dbo_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_p3.png",
plot = dbo_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.48598694801331
8.0.3 Fósforo total
(ptot <- ggplot(plan_wide_19902020,
aes(CODIGO,
fosforo_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Fósforo total no período 1990-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
trans = "log10")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)## Warning: Transformation introduced infinite values in continuous y-axis## Warning: Removed 134 rows containing non-finite values (stat_boxplot).
## Removed 134 rows containing non-finite values (stat_boxplot).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 47 rows containing missing values (position_quasirandom).## Warning: Removed 31 rows containing missing values (position_quasirandom).## Warning: Removed 56 rows containing missing values (position_quasirandom).
Time for this code chunk to
run: 1.27753710746765
(ptot_p1<-ggplot(plan_wide_19902020%>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
fosforo_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Fósforo total no período 1990-2000",
x="Estação",
y="mg/L")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
trans = "log10")+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.702898979187012
(ptot_p2 <- ggplot(plan_wide_19902020%>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
fosforo_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Fósforo total no período 2000-2010",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
trans = "log10")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.832069873809814
(ptot_p3 <- ggplot(plan_wide_19902020%>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
fosforo_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Fósforo total no período 2010-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
trans = "log10")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.819187879562378
grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3)
Time
for this code chunk to run: 1.95563292503357
(sum_ptot_p1 <- plan_wide_19902020 %>%
select(CODIGO, fosforo_total, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(fosforo_total, na.rm = TRUE),
q1 =
quantile(fosforo_total, 0.25, na.rm = TRUE),
median =
median(fosforo_total, na.rm = TRUE),
mean =
mean(fosforo_total, na.rm= TRUE),
q3 =
quantile(fosforo_total, 0.75, na.rm = TRUE),
max =
max(fosforo_total, na.rm = TRUE)))## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.0097 0.0593 0.0881 0.123 0.14 0.863
## 2 87398900 0.0023 0.0468 0.0678 0.0747 0.0883 0.247
## 3 87398950 0.0202 0.0544 0.0737 0.0751 0.0904 0.179
## 4 87398980 0.01 0.0254 0.0547 0.0708 0.114 0.189
## 5 87405500 0.017 0.171 0.281 0.417 0.492 2.32
## 6 87406900 0.156 0.270 0.508 0.785 1.07 2.79
## 7 87409900 0.107 0.258 0.384 0.489 0.712 1.53(sum_ptot_p2 <- plan_wide_19902020 %>%
select(CODIGO, fosforo_total, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(fosforo_total, na.rm = TRUE),
q1 =
quantile(fosforo_total, 0.25, na.rm = TRUE),
median =
median(fosforo_total, na.rm = TRUE),
mean =
mean(fosforo_total, na.rm= TRUE),
q3 =
quantile(fosforo_total, 0.75, na.rm = TRUE),
max =
max(fosforo_total, na.rm = TRUE)))## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.025 0.094 0.131 0.148 0.16 0.637
## 2 87398900 0.015 0.0764 0.104 0.140 0.164 0.646
## 3 87398950 0.036 0.116 0.171 0.180 0.207 0.485
## 4 87398980 0.0115 0.052 0.076 0.101 0.103 1
## 5 87405500 0.046 0.261 0.406 0.547 0.681 1.98
## 6 87406900 0.056 0.338 0.599 0.752 0.967 3.49
## 7 87409900 0.043 0.325 0.624 0.677 0.989 1.57(sum_ptot_p3 <- plan_wide_19902020 %>%
select(CODIGO, fosforo_total, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(fosforo_total, na.rm = TRUE),
q1 =
quantile(fosforo_total, 0.25, na.rm = TRUE),
median =
median(fosforo_total, na.rm = TRUE),
mean =
mean(fosforo_total, na.rm= TRUE),
q3 =
quantile(fosforo_total, 0.75, na.rm = TRUE),
max =
max(fosforo_total, na.rm = TRUE)))## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.061 0.118 0.163 0.166 0.186 0.381
## 2 87398900 0.057 0.0935 0.130 0.163 0.168 0.444
## 3 87398950 0.07 0.132 0.156 0.292 0.221 3.11
## 4 87398980 0.019 0.0625 0.106 0.144 0.170 0.59
## 5 87405500 0.013 0.187 0.332 0.361 0.45 0.803
## 6 87406900 0.089 0.254 0.364 0.448 0.560 1.26
## 7 87409900 0.203 0.259 0.369 0.488 0.564 1.7Time for this code chunk to run: 0.172072887420654
ggsave("ptot.png",
units = c("px"),
width = 4500,
height = 2993,
plot = ptot,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_p1.png",
plot = ptot_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_p2.png",
plot = ptot_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_p3.png",
plot = ptot_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.63755011558533
8.0.4 Escherichia coli
ecoli__class <- function() {
list(annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb") #classe 1
)
}
(ecoli <- ggplot(plan_wide_19902020,
aes(CODIGO,
E_coli))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Escherichia coli no período 1990-2020",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
# n.breaks = 9,
n.breaks = 6,
limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
max(plan_wide_19902020$E_coli, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()+
theme(
axis.text.y = element_text(
angle = 90,
# size=15,
# face=2
)
)
)
Time for this
code chunk to run: 1.31974911689758
(ecoli_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
E_coli))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Escherichia coli no período 1990-2000",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
max(plan_wide_19902020$E_coli, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.609876155853271
(ecoli_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
E_coli))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Escherichia coli no período 2000-2010",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
max(plan_wide_19902020$E_coli, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.600017070770264
(ecoli_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
E_coli))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Escherichia coli no período 2010-2020",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
max(plan_wide_19902020$E_coli, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.69613790512085
grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3)
Time
for this code chunk to run: 2.06048989295959
(sum_ecoli_p1 <- plan_wide_19902020 %>%
select(CODIGO, E_coli, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(E_coli,
na.rm = TRUE),
q1 =
quantile(E_coli, 0.25,
na.rm = TRUE),
median =
median(E_coli,
na.rm = TRUE),
mean =
mean(E_coli,
na.rm= TRUE),
q3 =
quantile(E_coli, 0.75,
na.rm = TRUE),
max =
max(E_coli,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 32 136 240 854. 720 19200
## 2 87398900 16 68 160 548. 480 7760
## 3 87398950 2.4 12.8 268 4039. 10000 28000
## 4 87398980 4 160 243. 2907. 446 25600
## 5 87405500 1.6 12.8 24 545. 128 18400
## 6 87406900 13.6 61.6 192 718. 414 12800
## 7 87409900 2.4 12.8 64 97.7 128 720(sum_ecoli_p2 <- plan_wide_19902020 %>%
select(CODIGO, E_coli, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(E_coli,
na.rm = TRUE),
q1 =
quantile(E_coli, 0.25,
na.rm = TRUE),
median =
median(E_coli,
na.rm = TRUE),
mean =
mean(E_coli,
na.rm= TRUE),
q3 =
quantile(E_coli, 0.75,
na.rm = TRUE),
max =
max(E_coli,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 21.6 91 150 1335. 308 27200
## 2 87398900 11 70 133. 444. 414. 2600
## 3 87398950 20 400 720 935. 1120 5500
## 4 87398980 24 110. 195 410. 289. 8800
## 5 87405500 4.7 162 2400 25445. 12950 490000
## 6 87406900 8 172 12800 66370. 62300 650000
## 7 87409900 16 7355. 35500 72440. 68750 460000(sum_ecoli_p3 <- plan_wide_19902020 %>%
select(CODIGO, E_coli, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(E_coli,
na.rm = TRUE),
q1 =
quantile(E_coli, 0.25,
na.rm = TRUE),
median =
median(E_coli,
na.rm = TRUE),
mean =
mean(E_coli,
na.rm= TRUE),
q3 =
quantile(E_coli, 0.75,
na.rm = TRUE),
max =
max(E_coli,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 90 155. 260 409. 451 2420
## 2 87398900 10 52.8 107 245. 313 1553.
## 3 87398950 108. 250 487 1424. 1553. 10462
## 4 87398980 40.8 140. 242. 529. 738. 2400
## 5 87405500 632 8965 19232. 109992. 70750 1400000
## 6 87406900 1440 23100 34500 230828. 140500 3400000
## 7 87409900 2000 20100 38400 83128. 83680 345000Time for this code chunk to run: 0.218228101730347
ggsave("ecoli.png",
plot = ecoli,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_p1.png",
plot = ecoli_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_p2.png",
plot = ecoli_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_p3.png",
plot = ecoli_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.49845099449158
8.0.5 Nitrogênio amoniacal
(namon <- ggplot(plan_wide_19902020,
aes(CODIGO,
nitro_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Nitrogênio amoniacal no período 1990-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time for this code
chunk to run: 1.50934982299805
(namon_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
nitro_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Nitrogênio amoniacal no período 1990-2000",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.948965787887573
(namon_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
nitro_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Nitrogênio amoniacal no período 2000-2010",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.590787887573242
(namon_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
nitro_total))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Nitrogênio amoniacal no período 2010-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.550995111465454
grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3)
Time
for this code chunk to run: 1.93264007568359
(sum_namon_p1 <- plan_wide_19902020 %>%
select(CODIGO, nitro_total, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(nitro_total,
na.rm = TRUE),
q1 =
quantile(nitro_total, 0.25,
na.rm = TRUE),
median =
median(nitro_total,
na.rm = TRUE),
mean =
mean(nitro_total,
na.rm= TRUE),
q3 =
quantile(nitro_total, 0.75,
na.rm = TRUE),
max =
max(nitro_total,
na.rm = TRUE),
n =
length(nitro_total)
)
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 0.44 0.842 1.00 1.22 1.34 3.81 101
## 2 87398900 0.22 0.82 1 1.09 1.25 4.86 101
## 3 87398950 0.51 0.83 1.02 1.06 1.19 2.16 68
## 4 87398980 0.549 0.68 0.755 0.872 1.01 1.85 30
## 5 87405500 0.51 1.53 2.94 5.27 6.77 21.6 97
## 6 87406900 1.34 2.60 4.56 7.58 11.2 29.1 32
## 7 87409900 0.5 1.98 4.29 5.18 7.01 19.6 65(sum_namon_p2 <- plan_wide_19902020 %>%
select(CODIGO, nitro_total, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(nitro_total,
na.rm = TRUE),
q1 =
quantile(nitro_total, 0.25,
na.rm = TRUE),
median =
median(nitro_total,
na.rm = TRUE),
mean =
mean(nitro_total,
na.rm= TRUE),
q3 =
quantile(nitro_total, 0.75,
na.rm = TRUE),
max =
max(nitro_total,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.18 0.885 0.992 1.80 1.46 23.2
## 2 87398900 0.48 0.894 1.13 1.38 1.57 7.92
## 3 87398950 0.57 1.26 1.45 1.43 1.71 1.98
## 4 87398980 0.19 0.685 0.79 1.05 1.10 5.2
## 5 87405500 0.968 2 3.29 5.45 6.60 21.7
## 6 87406900 0.77 2.4 4.54 7.30 10.2 39.1
## 7 87409900 1.62 2.5 6.97 7.92 10.6 21.5(sum_namon_p3 <- plan_wide_19902020 %>%
select(CODIGO, nitro_total, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(nitro_total,
na.rm = TRUE),
q1 =
quantile(nitro_total, 0.25,
na.rm = TRUE),
median =
median(nitro_total,
na.rm = TRUE),
mean =
mean(nitro_total,
na.rm= TRUE),
q3 =
quantile(nitro_total, 0.75,
na.rm = TRUE),
max =
max(nitro_total,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.222 0.89 1.11 1.24 1.41 2.56
## 2 87398900 0.095 0.883 1.02 1.29 1.40 4.25
## 3 87398950 0.612 1.04 1.43 1.90 2.06 9.5
## 4 87398980 0.216 0.973 1.12 1.22 1.58 2.32
## 5 87405500 1.12 2.03 3.14 4.50 5.93 22.0
## 6 87406900 1.37 2.40 5.58 6.47 7.58 25
## 7 87409900 1.11 3 6.15 7.29 7.75 36Time for this code chunk to run: 0.152504205703735
ggsave("namon.png",
units = c("px"),
width = 4500,
height = 2993,
plot = namon,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_p1.png",
plot = namon_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_p2.png",
plot = namon_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_p3.png",
plot = namon_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.70311307907104
8.0.6 Turbidez
(turb <- ggplot(plan_wide_19902020,
aes(CODIGO,
turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Turbidez no período 1990-2020",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.05)),
n.breaks = 16,
limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
# 500
max(plan_wide_19902020$turbidez, na.rm = TRUE)
),
# trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time for this code chunk
to run: 1.36168098449707
(turb_line <- plan_wide_19902020 %>%
filter(ANO_COLETA > "1990" &
ANO_COLETA <= "2020") %>%
select(CODIGO, turbidez, DATA_COLETA, periodo) %>%
group_by(CODIGO) %>%
ggplot(
aes(x = DATA_COLETA,
y = turbidez,
color = CODIGO
))+
geom_line(
# aes(color = CODIGO),
na.rm = TRUE)+
geom_point(
# aes(color = CODIGO),
na.rm = TRUE)+
scale_x_date(
limits = as.Date(c(
"1990-01-01",
"2021-01-01"
# NA #pode usar NA também
)),
expand = c(0.0, 0.0),
date_breaks = "10 years",
minor_breaks = "5 years",
date_labels = "%Y",
)+
# geom_smooth(
# # aes(color = CODIGO),
# method = "lm",
# # formula = y ~ poly(x, 2),
# # span = 0.2,
# se = TRUE, #se deixar TRUE gera o intervalo de confiança de 95%
# aes(group = 1),
# alpha =.5,
# na.rm = TRUE,
# size = 0.3,
# # fullrange = TRUE,
# # show.legend = TRUE
# )+
# stat_smooth(
# geom = "smooth",
# # span = 0.2,
# se = FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
# # aes(group = 1),
# # alpha =.5,
# na.rm = TRUE,
# # size = 0.3,
# fullrange = TRUE,
# show.legend = TRUE
# )+
facet_wrap(
~CODIGO,
nrow = 4,
)+
theme_bw()
)
Time
for this code chunk to run: 1.50534391403198
(turb_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Turbidez no período 1990-2000",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
max(plan_wide_19902020$turbidez, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 1.19833707809448
(turb_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Turbidez no período 2000-2010",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
max(plan_wide_19902020$turbidez, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.662497043609619
(turb_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Turbidez no período 2010-2020",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
max(plan_wide_19902020$turbidez, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.589815855026245
grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3)
Time
for this code chunk to run: 1.55097508430481
(sum_turb_p1 <- plan_wide_19902020 %>%
select(CODIGO, turbidez, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(turbidez,
na.rm = TRUE),
q1 =
quantile(turbidez, 0.25,
na.rm = TRUE),
median =
median(turbidez,
na.rm = TRUE),
mean =
mean(turbidez,
na.rm= TRUE),
q3 =
quantile(turbidez, 0.75,
na.rm = TRUE),
max =
max(turbidez,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 6.2 19 34.5 63.5 67 461
## 2 87398900 9 19 49.5 61.5 73.8 460
## 3 87398950 9.6 16 22 33.3 48.8 144
## 4 87398980 16 32.8 43 66.8 90.5 190
## 5 87405500 8.5 23.5 47 47.5 58 159
## 6 87406900 33 54.8 67 77.7 81.5 199
## 7 87409900 5.8 15 25 32.2 48 76(sum_turb_p2 <- plan_wide_19902020 %>%
select(CODIGO, turbidez, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(turbidez,
na.rm = TRUE),
q1 =
quantile(turbidez, 0.25,
na.rm = TRUE),
median =
median(turbidez,
na.rm = TRUE),
mean =
mean(turbidez,
na.rm= TRUE),
q3 =
quantile(turbidez, 0.75,
na.rm = TRUE),
max =
max(turbidez,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 9 41.2 55.5 71.1 74.2 428
## 2 87398900 39 57 78 107. 116. 475
## 3 87398950 39 47 64 96.5 90 330
## 4 87398980 24 37 50 64.5 87 176
## 5 87405500 32 46 63.5 70.3 76 341
## 6 87406900 35 49 62 69.9 75.5 284
## 7 87409900 40 45 60 70.4 90 151(sum_turb_p3 <- plan_wide_19902020 %>%
select(CODIGO, turbidez, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(turbidez,
na.rm = TRUE),
q1 =
quantile(turbidez, 0.25,
na.rm = TRUE),
median =
median(turbidez,
na.rm = TRUE),
mean =
mean(turbidez,
na.rm= TRUE),
q3 =
quantile(turbidez, 0.75,
na.rm = TRUE),
max =
max(turbidez,
na.rm = TRUE))
) ## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 8.52 16.4 29 33.3 43 85
## 2 87398900 14.8 39.2 48.3 66.7 73.4 299
## 3 87398950 16 29.9 41 51.6 65 230
## 4 87398980 11 19.4 33.6 39.5 42.2 110.
## 5 87405500 10.0 29.0 41 42.9 54.5 131
## 6 87406900 9.62 23 39 41.2 52 122
## 7 87409900 9.68 22.0 34.0 40.5 47 182.Time for this code chunk to run: 0.188423156738281
ggsave("turb.png",
units = c("px"),
width = 4500,
height = 2993,
plot = turb,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_p1.png",
plot = turb_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_p2.png",
plot = turb_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_p3.png",
plot = turb_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 6.14089012145996
8.0.7 pH
(pH <- ggplot(plan_wide_19902020,
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "pH no período 1990-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time for this code chunk to
run: 1.50695610046387
(pH_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "pH no período 1990-2000",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.595287084579468
(pH_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "pH no período 2000-2010",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.620581150054932
(pH_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "pH no período 2010-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.497467994689941
grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3)
Time
for this code chunk to run: 1.63380193710327
(sum_pH_p1 <- plan_wide_19902020 %>%
select(CODIGO, pH, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(pH,
na.rm = TRUE),
q1 =
quantile(pH, 0.25,
na.rm = TRUE),
median =
median(pH,
na.rm = TRUE),
mean =
mean(pH,
na.rm= TRUE),
q3 =
quantile(pH, 0.75,
na.rm = TRUE),
max =
max(pH,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 5 6.18 6.59 6.51 6.82 7.9
## 2 87398900 5.2 6 6.3 6.33 6.63 7.9
## 3 87398950 5.4 6.29 6.4 6.49 6.72 8.1
## 4 87398980 5.3 5.93 6.2 6.16 6.3 7.3
## 5 87405500 5 6.3 6.4 6.47 6.7 9.3
## 6 87406900 5.5 6.18 6.45 6.43 6.8 7.3
## 7 87409900 4.5 6.2 6.4 6.44 6.7 7.4(sum_pH_p2 <- plan_wide_19902020 %>%
select(CODIGO, pH, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(pH,
na.rm = TRUE),
q1 =
quantile(pH, 0.25,
na.rm = TRUE),
median =
median(pH,
na.rm = TRUE),
mean =
mean(pH,
na.rm= TRUE),
q3 =
quantile(pH, 0.75,
na.rm = TRUE),
max =
max(pH,
na.rm = TRUE))
) ## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 5.3 6.3 6.6 6.59 6.88 7.9
## 2 87398900 5.5 6.4 6.65 6.63 6.9 7.5
## 3 87398950 6 6.6 6.8 6.89 7.25 7.6
## 4 87398980 5.8 6.3 6.5 6.63 7 7.5
## 5 87405500 5.2 6.4 6.6 6.68 6.9 8.3
## 6 87406900 5.5 6.4 6.7 6.66 6.9 8.6
## 7 87409900 5.8 6.5 6.8 6.77 7 8.4(sum_pH_p3 <- plan_wide_19902020 %>%
select(CODIGO, pH, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(pH,
na.rm = TRUE),
q1 =
quantile(pH, 0.25,
na.rm = TRUE),
median =
median(pH,
na.rm = TRUE),
mean =
mean(pH,
na.rm= TRUE),
q3 =
quantile(pH, 0.75,
na.rm = TRUE),
max =
max(pH,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 5.47 6.28 6.42 6.47 6.60 7.3
## 2 87398900 5.68 6.36 6.5 6.57 6.84 7.4
## 3 87398950 5.71 6.28 6.46 6.46 6.68 7
## 4 87398980 5.42 6.10 6.36 6.39 6.6 7.2
## 5 87405500 5.64 6.34 6.5 6.49 6.7 7.01
## 6 87406900 5.6 6.4 6.48 6.51 6.77 7.3
## 7 87409900 5.59 6.46 6.6 6.57 6.76 7.2Time for this code chunk to run: 0.171074867248535
ggsave("pH.png",
units = c("px"),
width = 4500,
height = 2993,
plot = pH,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_p1.png",
plot = pH_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_p2.png",
plot = pH_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_p3.png",
plot = pH_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time for
this code chunk to run: 5.65565991401672
8.0.8 Sólidos totais
(SolTot <- ggplot(plan_wide_19902020,
aes(CODIGO,
solidos_totais))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Sólidos totais no período 1990-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time for this code
chunk to run: 1.55493092536926
(SolTot_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
solidos_totais))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Sólidos totais no período 1990-2000",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.573714017868042
(SolTot_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
solidos_totais))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Sólidos totais no período 2000-2010",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.681281089782715
(SolTot_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
solidos_totais))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Sólidos totais no período 2010-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.48236608505249
grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3)
Time
for this code chunk to run: 1.56048107147217
(sum_SolTot_p1 <- plan_wide_19902020 %>%
select(CODIGO, solidos_totais, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(solidos_totais,
na.rm = TRUE),
q1 =
quantile(solidos_totais, 0.25,
na.rm = TRUE),
median =
median(solidos_totais,
na.rm = TRUE),
mean =
mean(solidos_totais,
na.rm= TRUE),
q3 =
quantile(solidos_totais, 0.75,
na.rm = TRUE),
max =
max(solidos_totais,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 46 84.5 95 122. 120 510
## 2 87398900 18 74.5 97 111. 122. 474
## 3 87398950 10 76.5 91 90.9 106. 155
## 4 87398980 48 63.5 81.5 104. 126. 337
## 5 87405500 70 101 121 133. 151 361
## 6 87406900 89 118 155 165. 210 279
## 7 87409900 20 99.5 122 128. 143 381(sum_SolTot_p2 <- plan_wide_19902020 %>%
select(CODIGO, solidos_totais, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(solidos_totais,
na.rm = TRUE),
q1 =
quantile(solidos_totais, 0.25,
na.rm = TRUE),
median =
median(solidos_totais,
na.rm = TRUE),
mean =
mean(solidos_totais,
na.rm= TRUE),
q3 =
quantile(solidos_totais, 0.75,
na.rm = TRUE),
max =
max(solidos_totais,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 28 80 100 111. 123. 412
## 2 87398900 42 82 102. 128. 140. 489
## 3 87398950 46 94.2 108. 126. 127. 318
## 4 87398980 40 61 77 85.3 96 228
## 5 87405500 48 102 133 148. 170. 522
## 6 87406900 50 109 134. 154. 170. 670
## 7 87409900 56 112. 156 167. 190. 599(sum_SolTot_p3 <- plan_wide_19902020 %>%
select(CODIGO, solidos_totais, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(solidos_totais,
na.rm = TRUE),
q1 =
quantile(solidos_totais, 0.25,
na.rm = TRUE),
median =
median(solidos_totais,
na.rm = TRUE),
mean =
mean(solidos_totais,
na.rm= TRUE),
q3 =
quantile(solidos_totais, 0.75,
na.rm = TRUE),
max =
max(solidos_totais,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 61 69 90 82.8 96 101
## 2 87398900 41 77 104 120. 127 308
## 3 87398950 45 93 101 109. 117 221
## 4 87398980 55 62.8 80 79.9 95 109
## 5 87405500 83 89.2 108. 124. 162. 195
## 6 87406900 50 106 117 135. 163 246
## 7 87409900 75 103 115 131. 145 251Time for this code chunk to run: 0.156016111373901
ggsave("SolTot.png",
units = c("px"),
width = 4500,
height = 2993,
plot = SolTot,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_p1.png",
plot = SolTot_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_p2.png",
plot = SolTot_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_p3.png",
plot = SolTot_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.83642506599426
8.0.9 IQA
Time for this code chunk to
run: 1.05483984947205
Time
for this code chunk to run: 0.499975919723511
Time
for this code chunk to run: 0.484118938446045
Time
for this code chunk to run: 0.421229839324951
grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3)
Time
for this code chunk to run: 1.35080194473267
(sum_IQA_p1 <- plan_wide_19902020 %>%
select(CODIGO, IQA, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(IQA,
na.rm = TRUE),
q1 =
quantile(IQA, 0.25,
na.rm = TRUE),
median =
median(IQA,
na.rm = TRUE),
mean =
mean(IQA,
na.rm= TRUE),
q3 =
quantile(IQA, 0.75,
na.rm = TRUE),
max =
max(IQA,
na.rm = TRUE),
n =
length(IQA)
)
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 27.0 35.7 40.9 40.7 46.2 52.2 101
## 2 87398900 27.8 37.9 42.9 43.0 48.0 58.5 101
## 3 87398950 32.8 36.8 41.4 43.2 48.6 61.9 68
## 4 87398980 29.2 35.8 40.4 40.3 44.8 51.9 30
## 5 87405500 24.8 34.9 41.2 40.3 46.9 57.6 97
## 6 87406900 24.7 31.3 37.8 37.4 44.4 49.0 32
## 7 87409900 23.6 31.9 37.1 38.8 46.2 55.4 65(sum_IQA_p2 <- plan_wide_19902020 %>%
select(CODIGO, IQA, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(IQA,
na.rm = TRUE),
q1 =
quantile(IQA, 0.25,
na.rm = TRUE),
median =
median(IQA,
na.rm = TRUE),
mean =
mean(IQA,
na.rm= TRUE),
q3 =
quantile(IQA, 0.75,
na.rm = TRUE),
max =
max(IQA,
na.rm = TRUE),
n =
length(IQA)
)
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 27.8 34.6 40.0 39.5 43.5 48.7 75
## 2 87398900 28.5 35.1 37.6 38.3 40.6 48.5 77
## 3 87398950 21.1 29.4 32.7 32.8 36.8 44.0 30
## 4 87398980 24.5 35.7 39.4 39.5 43.4 52.1 66
## 5 87405500 19.8 28.7 31.5 31.9 35.7 48.8 78
## 6 87406900 17.1 25.3 29.0 29.5 32.8 44.1 79
## 7 87409900 16.2 20.5 26.1 25.0 29.8 33.1 31(sum_IQA_p3 <- plan_wide_19902020 %>%
select(CODIGO, IQA, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
# ?as_factor(CODIGO) %>%
group_by(CODIGO) %>%
summarize(
min =
min(IQA,
na.rm = TRUE),
q1 =
quantile(IQA, 0.25,
na.rm = TRUE),
median =
median(IQA,
na.rm = TRUE),
mean =
mean(IQA,
na.rm= TRUE),
q3 =
quantile(IQA, 0.75,
na.rm = TRUE),
max =
max(IQA,
na.rm = TRUE),
n =
length(IQA),
NAs =
sum(is.na(IQA))
) %>%
mutate(
"%NA" = NAs/n*100
)
)## # A tibble: 7 x 10
## CODIGO min q1 median mean q3 max n NAs `%NA`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int> <dbl>
## 1 87398500 40.2 42.5 45.4 44.2 45.5 47.2 34 29 85.3
## 2 87398900 34.1 38.6 41.2 40.2 42.9 44.4 36 32 88.9
## 3 87398950 36.7 39.5 42.4 41.5 44.4 44.6 35 31 88.6
## 4 87398980 40.0 40.0 40.0 40.0 40.0 40.0 28 27 96.4
## 5 87405500 30.8 31.6 32.5 32.5 33.3 34.1 33 31 93.9
## 6 87406900 22.9 24.4 25.9 25.3 26.5 27.2 35 32 91.4
## 7 87409900 24.1 25.1 27.3 26.9 28.2 29.7 37 32 86.5Time for this code chunk to run: 0.169561862945557
ggsave("iqa.png",
units = c("px"),
width = 4500,
height = 2993,
plot = iqa,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_p1.png",
plot = iqa_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_p2.png",
plot = iqa_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_p3.png",
plot = iqa_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.13018298149109
8.1 Testando coisas
8.1.1 Correlação
parametros_IQA %>%
select(-CODIGO, -nitro_total) %>%
rename(
CE = Condutividade,
OD = oxigenio_dissolvido,
ST = solidos_totais,
Turb = turbidez,
Temp = temp_agua,
Ptot = fosforo_total,
NAmon = nitro_amon,
NTK = nitro_kjeldahl
) %>%
ggcorr(
method = "complete.obs",
# "pearson",
# "pairwise",
name = "Correlação",
label = TRUE,
label_alpha = TRUE,
digits = 3,
low = "#3B9AB2",
mid = "#EEEEEE",
high = "#F21A00",
# palette = "RdYlBu",
layout.exp = 0,
legend.position = "left",
label_round = 3,
# legend.size = 18,
geom = "tile",
nbreaks = 10,
)+
labs(title = "Correlação entre parâmetros físico-químicos na\nBacia Hidrográfica do rio Gravataí no período 1990-2020")+
theme_linedraw()+
theme(
legend.position = c(0.15, 0.6),
legend.title = element_text(size = 16),
legend.text = element_text(size = 14),
# legend.spacing = unit(element_text(),
# units = 5)
plot.title = element_text(hjust = 0.5,
size = 16)
)
correlação-parametros-qualidade-agua-gravataí no período 1990-2020
# Gráfico das correlações entre todos os parâmetros com significância
correl_IQA <- parametros_IQA %>%
select(-CODIGO) %>%
ggpairs(title = "Correlação entre parâmetros que compõem o IQA",
axisLabels = "show")Time for this code chunk to run: 0.713647842407227
8.1.2 Condutividade elétrica
(cond_elet <- ggplot(plan_wide_19902020,
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Condutividade elétrica no período 1990-2020",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time for
this code chunk to run: 1.24694895744324
(cond_elet_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Condutividade elétrica no período 1990-2000",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.527585983276367
(cond_elet_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Condutividade elétrica no período 2000-2010",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.521561145782471
(cond_elet_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Condutividade elétrica no período 2010-2020",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.492647886276245
grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3)
Time
for this code chunk to run: 1.45916795730591
(sum_cond_elet_p1 <- plan_wide_19902020 %>%
select(CODIGO, Condutividade, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Condutividade,
na.rm = TRUE),
q1 =
quantile(Condutividade, 0.25,
na.rm = TRUE),
median =
median(Condutividade,
na.rm = TRUE),
mean =
mean(Condutividade,
na.rm= TRUE),
q3 =
quantile(Condutividade, 0.75,
na.rm = TRUE),
max =
max(Condutividade,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 9.4 51.1 67 75.1 83.2 340
## 2 87398900 10 41.5 51 55.3 64.2 160
## 3 87398950 9 41.5 51.5 60.1 69.5 160
## 4 87398980 11.3 42.4 52.0 53.0 67.0 83.8
## 5 87405500 25 68.7 88.2 130. 170 560
## 6 87406900 52 88.4 133. 193. 256. 576
## 7 87409900 29 80 110. 134. 168. 460(sum_cond_elet_p2 <- plan_wide_19902020 %>%
select(CODIGO, Condutividade, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Condutividade,
na.rm = TRUE),
q1 =
quantile(Condutividade, 0.25,
na.rm = TRUE),
median =
median(Condutividade,
na.rm = TRUE),
mean =
mean(Condutividade,
na.rm= TRUE),
q3 =
quantile(Condutividade, 0.75,
na.rm = TRUE),
max =
max(Condutividade,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 11.9 67.0 82.6 84.8 102. 164.
## 2 87398900 11 44.4 52.3 57.1 72.6 136.
## 3 87398950 39.8 58.4 76 82.3 98.3 160
## 4 87398980 9.4 42.4 49.7 51.5 62 114.
## 5 87405500 17 77.5 107 142. 171. 679
## 6 87406900 23.1 85.6 124. 164. 199. 619
## 7 87409900 56.1 114. 177 200. 242 454(sum_cond_elet_p3 <- plan_wide_19902020 %>%
select(CODIGO, Condutividade, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Condutividade,
na.rm = TRUE),
q1 =
quantile(Condutividade, 0.25,
na.rm = TRUE),
median =
median(Condutividade,
na.rm = TRUE),
mean =
mean(Condutividade,
na.rm= TRUE),
q3 =
quantile(Condutividade, 0.75,
na.rm = TRUE),
max =
max(Condutividade,
na.rm = TRUE),
n =
length(Condutividade))
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 0.01 68.5 80.2 80.4 99.5 125. 34
## 2 87398900 39.7 53.4 58.3 61.1 65.5 103 36
## 3 87398950 40.9 64.7 70.1 76.1 82.5 195. 35
## 4 87398980 43.2 51.7 54.0 56.3 61.0 78.9 28
## 5 87405500 47 85.8 121. 146. 209. 286 33
## 6 87406900 62.7 95.9 142. 163. 216. 354. 35
## 7 87409900 65.7 121. 159. 179. 245. 498. 37# plan_wide_19902020 %>%
# select(CODIGO, IQA) %>%
# group_by(CODIGO) %>%
# summarize(
# min =
# min(IQA,
# na.rm = TRUE),
# q1 =
# quantile(IQA, 0.25,
# na.rm = TRUE),
# median =
# median(IQA,
# na.rm = TRUE),
# mean =
# mean(IQA,
# na.rm= TRUE),
# q3 =
# quantile(IQA, 0.75,
# na.rm = TRUE),
# max =
# max(IQA,
# na.rm = TRUE))Time for this code chunk to run: 0.181611061096191
ggsave("cond_elet.png",
units = c("px"),
width = 4500,
height = 2993,
plot = cond_elet,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_p1.png",
plot = cond_elet_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_p2.png",
plot = cond_elet_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_p3.png",
plot = cond_elet_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.74093794822693
---
title: "TCC"
author: "Leonardo Fernandes Wink"
date: "`r format(Sys.time(), '%d/%m/%Y')`"
output:
  html_document: 
    highlight: haddock
    keep_md: yes
    number_sections: yes
    theme: flatly
    toc: yes
    toc_float:
      collapsed: no
      smooth_scroll: no
    fig_width: 10
    fig_height: 6.66
    fig_caption: yes
    code_download: true
  pdf_document:
    toc: yes
  word_document: 
    toc: yes
    keep_md: yes
  github_document:
    html_preview: true
always_allow_html: yes
editor_options: 
  chunk_output_type: console
fig.align: center
---

```{r Rotina pra toda vez que abrir o documento, echo = FALSE}
# Abrir o GitHub Desktop
# Verificar se há pull pra ser feito
# Abrir o RStudio
```

# Brief explanation

Every boxplot means a monitoring point (Ponto de monitoramento (or PM) in portuguese). My goal here is to analyze the evolution between decades of each water quality parameter that compounds the Water Quality Index (WQI).

The river flows in the east-west direction as shown in the image below.

![](images/paste-7AD7027F.png)

The logic behind the sorting in the boxplots is because of 2 main reasons:

1.  The original monitoring point isn't easy to understand (8 digits, like 87409900)
2.  Changing the original nomenclature to PM1, PM2 (...) makes it easier to understand that the last point has water contributions of every other point upstream.

Some features that I want to add:
- If the parameter is x, then use x's classes (with its own classes background color plotted)
- Define the timescale, should act just like a filter

```{r p1 example}
# plan_wide_19902020 %>%
#   filter(ANO_COLETA > "1990" &
#          ANO_COLETA <= "2000")
```

# Anotações de coisas por fazer:

-   Descobrir como colocar as estações no sentido correto montante -\> jusante nos sumários

> 87398500, 87398980, 87398900, 87398950, 87405500, 87406900, 87409900

-   ~~Aprender a segmentar o meu dataset por períodos~~
-   aprender a criar uma nova coluna com a segmentação dos períodos
-   maybe use `~facet.grid`
-   aprender a colocar a legenda dentro do gráfico
    -   reduzir o tamanho da legenda
-   ~~corrigir os valores 0 de IQA pra NA~~
-   descobrir como conseguir a equação do lm
-   ~~aprender a pivotar o sumário~~ -\> meu sumário do google docs ta batendo direitinho com o do R
-   descobrir se há outros TCCs com disponibilização de códigos
-   `Namon` tá com com casa decimal `","` e `ptot` tá com `"."`
-   correlação forte entre condutividade e Namon/Ptot/DBO

| 1990-2000 | 2000-2010 | 2010-2020 |
|:---------:|:---------:|:---------:|
| 1990-2000 | 2000-2010 | 2010-2020 |

# Instalar os pacotes

```{r instalar pacotes}
# install.packages(tidyverse)
```

## acessar os pacotes

```{r Acessar os pacotes, message = FALSE, warning = TRUE}
# library(readr)
# library(rmarkdown)
# # library(qboxplot)
# library(readxl)
# library(pillar)
# library(dplyr)
# library(tidyverse)
# library(gapminder)
# library(knitr)
# library(kableExtra)
# library(ggpubr)
# library(gridExtra)
# library(modelsummary)
# library(gtsummary)
# library(GGally)
pacman::p_load(readr, rmarkdown, readxl,
               pillar, dplyr, tidyverse,
               gapminder, knitr, kableExtra,
               gridExtra, #modelsummary, 
               gtsummary, ggplot2,
               ggbeeswarm, GGally)
# pacman::p_load(tibbletime)
```

```{r cronometrando quanto tempo cada chunk leva}
knitr::knit_hooks$set(time_it = local({
   now <- NULL
   function(before, options) {
      if (before) {
         # record the current time before each chunk
         now <<- Sys.time()
      } else {
         # calculate the time difference after a chunk
         res <- difftime(Sys.time(), now)
         # return a character string to show the time
         paste("Time for this code chunk to run:", res)
      }
   }
}))

knitr::opts_chunk$set(time_it = TRUE)
```

```{r setup, include=FALSE}
# knitr::opts_chunk$set(echo = TRUE)
```

## importando a planilha

```{r Importando a planilha, echo = FALSE, message = TRUE, warning = FALSE}
plan_wide_19902020 <- read_delim("https://raw.githubusercontent.com/leonardofwink/TCC_gh/main/plan_wide_19902020.tsv",
                                 delim = "\t", 
                                 escape_double = FALSE,
                                 col_types = cols(
                                   Alcalinidade = col_double(),
                                   CODIGO = col_character(), 
                                   COORD_GEO_LAT_GRAU = col_double(),
                                   COORD_GEO_LONG_GRAU = col_double(),
                                   DATA_COLETA = col_date(format = "%d/%m/%Y"),
                                   Nitrato = col_double(), 
                                   Nitrito = col_double(),
                                   SDT = col_double(), 
                                   SST = col_double(),
                                   `Vazao` = col_double(), 
                                   `Vazao rio` = col_double()
                                 ),
                                 locale = locale(
                                   date_names = "pt", 
                                   decimal_mark = ",",
                                   grouping_mark = ""
                                 ),
                                 trim_ws = TRUE
) %>% 
  rename(
    E_coli = `Escherichia coli`,
    fosfato_orto = `Fosfato orto`,
    fosforo_total = `Fósforo total`,
    nitro_organico = `Nitrogênio orgânico`,
    nitro_amon = `Nitrogênio amoniacal`,
    nitro_kjeldahl = `Nitrogênio Kjeldahl`,
    nitro_total = `Nitrogênio total`,
    oxigenio_dissolvido = `Oxigênio dissolvido`,
    sat_OD = `%sat OD`,
    temp_agua = `Temperatura água`,
    temp_ar = `Temperatura ar`,
    transparencia_agua = `Transparência água`,
    vazao_rio = `Vazao rio`,
    coliformes_termo = `Coliformes termotol`,
    turbidez = Turbidez,
    solidos_totais = `Sólidos totais`,
  )

glimpse(plan_wide_19902020)
# teste <- plan_wide_19902020 %>%
#   dplyr::filter(DATA_COLETA >= as.POSIXct("2010-01-01")) #this works
# 
# teste$DATA_COLETA <- as.POSIXct(teste$DATA_COLETA)
# 
# teste %>% 
#   dplyr::arrange(DATA_COLETA)
# teste %>% 
#   filter_time(time_formula = '2013-01-01' ~ '2020-12-31')
# 
# 
# typeof(teste$DATA_COLETA)
# 
#   as_tbl_time(plan_wide_19902020, index = DATA_COLETA)
# str(plan_wide_19902020$DATA_COLETA)
```

```{r Visualização da planilha importada, echo = FALSE}
paged_table(plan_wide_19902020,
            options = list(rows.print = 15,
                           cols.print = 10))
```

# data wrangling

```{r data wrangling}
# Como há dados faltantes, no cálculo entre o produto das colunas, ele acaba interpretando como se fosse zero, mas na verdade é NA
plan_wide_19902020 <- plan_wide_19902020 %>% 
   mutate(IQA = ifelse(IQA == 0, NA, IQA))

parametros_IQA <- plan_wide_19902020 %>%
  select(CODIGO,
         pH,
         DBO,
         E_coli,
         nitro_amon,
         nitro_kjeldahl,
         nitro_total,
         fosforo_total,
         temp_agua,
         turbidez,
         solidos_totais,
         oxigenio_dissolvido,
         Condutividade)

write.csv(parametros_IQA,
          "./parametros_IQA.csv",
          row.names = FALSE)

plan_wide_19902020 %>% 
  select(starts_with("IQA_^")) %>% 
  mutate(
    TESTANDOIQA = prod()
  )
# library(performance)
# modelo <- plan_wide_19902020 %>% 
#   select(CODIGO, oxigenio_dissolvido, periodo) %>% 
#   group_by(CODIGO, periodo) %>% 
#   lm() %>% 
#   performance::check_distribution()
# # lm()
# 
# check_model(modelo)
# performance::check_autocorrelation(modelo)

```

```{r Códigos Git, echo = FALSE}
# cd myrepo
# ls
# head README.md
# git status
# git add README.md
# git commit -m "A commit from my local computer"
# 
# cd .. # voltar pro diretório acima
# rm -rf myrepo/ #remover/apagar a pasta myrepo
```

```{r Aprendendo Git, echo = FALSE}
# slides da bia que ajudam mt
# https://beatrizmilz.github.io/slidesR/git_rstudio/11-2021-ENCE.html#20
# aprendendo a sincronizar usando esse guia -> 
# https://happygitwithr-com.translate.goog/push-pull-github.html?_x_tr_sl=auto&_x_tr_tl=pt&_x_tr_hl=pt-BR
# library(usethis)
# usethis::create_github_token() criar um código pra acesso e sincronização between R e github

# gitcreds::gitcreds_set() 
# 
# use_git_config(user.name = "leonardofwink",
#                user.email = "leonardofwink@gmail.com")
# usethis::gh_token_help()

# Como mostrar os dados de um arquivo via Git/GitHub
# git clone https://github.com/leonardofwink/myrepo.git
# cd myrepo #acessa a pasta myrepo
# ls #lista os arquivos da pasta 
# head README.md #mostra as primeiras observações do arquivo

# Como mostrar os dados de um arquivo via R
# head(C:/Users/Léo/myrepo/README.md)

# Adicionar uma linha ao README.md e verificar se o Git percebe a mudança
# echo "A line I wrote on my local computer" >> README.md
# git status
## C:\Users\Léo\myrepo>git status
## On branch main
## Your branch is up to date with 'origin/main'.
## 
## Changes not staged for commit:
##   (use "git add <file>..." to update what will be committed)
##   (use "git restore <file>..." to discard changes in working directory)
##         **modified:   README.md**
## 
## no changes added to commit (use "git add" and/or "git commit -a")
```

# setting theme

```{r setting theme}
theme_grafs <- function(bg = "white", 
                        coloracao_letra = "black") {
  theme(
    plot.title = 
      element_text(
        hjust = 0.5,
        color = coloracao_letra,
        size = 19),
    
    axis.title.x = 
      # element_text(
      # color = coloracao_letra,
      # size = 15,
      # angle = 0,),
      element_blank(),
    axis.title.y = element_text(
      color = coloracao_letra,
      size = 15,
      angle = 90),
    
    axis.text.x = element_text(
      color = coloracao_letra,
      size = 17),
    axis.text.y = element_text(
      color = coloracao_letra,
      size = 17,
      angle = 0),
    
    strip.background = element_rect(fill = bg,
                                    linetype = 1,
                                    size = 0.5,
                                    color = "black"),
    strip.text = element_text(size = 17),
    panel.background = element_rect(fill = bg),
    plot.background = element_rect(fill = bg),
    plot.margin = margin(l = 5, r = 10,
                         b = 5, t = 5)
  )
}
```

# setting different timescales

```{r setting periodos, echo = FALSE}
plan_wide_19902020 <- plan_wide_19902020 %>% 
  # select(CODIGO, ANO_COLETA) %>% 
  mutate(
    periodo = if_else(
      ANO_COLETA <= 2000, 
      "1990-2000",
      if_else(
        ANO_COLETA <= 2010,
        "2000-2010",
        "2010-2020"
      )
    )
  )
```

# setting sumaries

```{r Sumários, echo = FALSE}
# plan_wide_19902020 %>%
#   as_tibble() %>% 
#   filter(ANO_COLETA > "1990" &
#            ANO_COLETA <= "2000") %>% 
#   select(colnames(parametros_IQA)) %>% 
#   group_by(CODIGO) %>% 
#   group_by(colnames(parametros_IQA)) %>% 
#   summarise_each(
#     funs( 
#       min = 
#         min(., 
#             na.rm = TRUE),
#       q1 = 
#         quantile(., 0.25, 
#                  na.rm = TRUE),
#       median = 
#         median(., 
#                na.rm = TRUE),
#       mean = 
#         mean(., 
#              na.rm= TRUE),
#       q3 = 
#         quantile(., 0.75, 
#                  na.rm = TRUE),
#       max = 
#         max(., 
#             na.rm = TRUE),
#       n = 
#         length(.)
#     )
#   ) %>% 
#   pivot_longer(
#        !CODIGO,
#        names_to = "parametro",
#        values_to = "valor"
#     ) %>% 
#     pivot_wider(names_from = CODIGO,
#                 values_from = valor) %>% 
#   group_by(parametro)



# p2 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2000" &
#          ANO_COLETA <= "2010")
# 
# p3 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2010" &
#          ANO_COLETA <= "2020")

# periodo = c(p1 <- plan_wide_19902020 %>% 
#   filter(ANO_COLETA > "1990" &
#            ANO_COLETA <= "2000"),
# 
# p2 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2000" &
#            ANO_COLETA <= "2010"),
# 
# p3 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2010" &
#            ANO_COLETA <= "2020"))

# sumario <- function(parametros = parametros, periodo){
#   plan_wide_19902020 %>%
#    select(CODIGO, ., ANO_COLETA) %>% 
#    # filter(ANO_COLETA>"1990" &
#    #          ANO_COLETA<="2000") %>% 
#    group_by(CODIGO) %>% 
#    summarize(
#      min = 
#        min(parametros, 
#            na.rm = TRUE),
#      q1 = 
#        quantile(parametros, 0.25, 
#                 na.rm = TRUE),
#      median = 
#        median(parametros, 
#               na.rm = TRUE),
#      mean = 
#        mean(parametros, 
#             na.rm= TRUE),
#      q3 = 
#        quantile(parametros, 0.75, 
#                 na.rm = TRUE),
#      max = 
#        max(parametros, 
#            na.rm = TRUE))
# }

# plan_wide_19902020 %>% 
#   sumario(parametros = DBO)

# sum_IQA_p1 <- plan_wide_19902020 %>%
#    select(CODIGO, IQA, ANO_COLETA) %>% 
#    filter(ANO_COLETA>"1990" &
#             ANO_COLETA<="2000") %>% 
#    group_by(CODIGO) %>% 
#    summarize(
#      min = 
#        min(IQA, 
#            na.rm = TRUE),
#      q1 = 
#        quantile(IQA, 0.25, 
#                 na.rm = TRUE),
#      median = 
#        median(IQA, 
#               na.rm = TRUE),
#      mean = 
#        mean(IQA, 
#             na.rm= TRUE),
#      q3 = 
#        quantile(IQA, 0.75, 
#                 na.rm = TRUE),
#      max = 
#        max(IQA, 
#            na.rm = TRUE))
```

# Parâmetros físico-químicos

### Oxigênio Dissolvido

```{r Gráfico OD facetted, echo = FALSE, warning=FALSE, message = FALSE, fig.cap="Oxigênio Dissolvido no período 1990-2020"}
(od <- plan_wide_19902020 %>% 
    ggplot(
      aes(
        x = CODIGO,
        y = oxigenio_dissolvido,
        # color = periodo,
        # fill = periodo
        )
    )+
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = -Inf, ymax = 2,
             alpha = 1,
             fill = "#ac5079")+ #>pior classe
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = 2, ymax = 4,
             alpha = 1,
             fill = "#eb5661")+ #classe 4
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = 4, ymax = 5,
             alpha = 1,
             fill = "#fcf7ab")+ #classe 3
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = 5, ymax = 6,
             alpha = 1,
             fill = "#70c18c")+ #classe 2
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin= 6, ymax = Inf,
             alpha = 1,
             fill = "#8dcdeb")+ #classe 1
    stat_boxplot(
      geom = 'errorbar',
      width = 0.3,
      position = position_dodge(width = 0.65)
    )+
    geom_boxplot(
      fill = '#F8F8FF',
      color = "black",
      outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
      width = 0.7
    )+
    facet_wrap(~periodo)+
    labs(
      title = "Oxigênio Dissolvido no período 1990-2020",
      x= NULL,
      y="mg/L"
    )+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(
      expand = expansion(mult = c(0,0)),
      n.breaks = 11,
      limits = c(-0.3,21)
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    # scale_fill_brewer(palette = "Set1")+
    scale_color_manual(name = "Período",
                       breaks = c("p1", "p2", "p3"),
                       values = c("black", "#303030", "#696969"),
                       labels = c("1990-2000", "2000-2010", "2010-2020")
    )+
    geom_smooth(
      method = "lm",
      se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
      aes(group = 1),
      alpha = .5,
      na.rm = TRUE,
      size = 1
    )+
  theme_grafs()
)
```


```{r Gráfico OD periodo 1, echo = FALSE, warning=FALSE, message = FALSE, fig.cap="Oxigênio Dissolvido no período 1990-2000"}
(od_p1 <- ggplot(plan_wide_19902020 %>% 
                    filter(ANO_COLETA > "1990" &
                              ANO_COLETA <= "2000"),
                 aes(CODIGO,
                     oxigenio_dissolvido)
)+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = -Inf, ymax = 2,
            alpha = 1,
            fill = "#ac5079")+ #>pior classe
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 2, ymax = 4,
            alpha = 1,
            fill = "#eb5661")+ #classe 4
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 4, ymax = 5,
            alpha = 1,
            fill = "#fcf7ab")+ #classe 3
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 5, ymax = 6,
            alpha = 1,
            fill = "#70c18c")+ #classe 2
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin= 6, ymax = Inf,
            alpha = 1,
            fill = "#8dcdeb")+ #classe 1
   stat_boxplot(
      geom = 'errorbar',
      width = 0.3,
      position = position_dodge(width = 0.65)
   )+
   geom_boxplot(
      fill = '#F8F8FF',
      color = "black",
      outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
      width = 0.7
   )+
   labs(
      title = "Oxigênio Dissolvido no período 1990-2000",
      x="Estação",
      y="mg/L"
   )+
   ggbeeswarm::geom_quasirandom(
      size = 1.2,
      alpha = .25,
      width = .07,
   )+
   scale_y_continuous(
      expand = expansion(mult = c(0,0)),
      n.breaks = 11,
      limits = c(-1,21)
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(
      method = "lm",
      se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
      aes(group = 1),
      alpha = .5,
      na.rm = TRUE,
      size = 1
   )+
   theme_grafs()
)
```


```{r Gráfico OD periodo 2, echo = FALSE, warning=FALSE, message = FALSE}
(od_p2 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2000" &
                             ANO_COLETA<="2010"),
                aes(CODIGO,
                    oxigenio_dissolvido))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=2,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=2,
             ymax=4,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=4,
             ymax=5,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=6,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=6,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Oxigênio Dissolvido no período 2000-2010",
         x="Estação",
         y=NULL)+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(
       expand = expansion(mult = c(0,0)),
       n.breaks = 11,
       limits = c(-1,21))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```


```{r Gráfico OD periodo 3, echo = FALSE, warning=FALSE, message = FALSE}
(od_p3 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2010" &
                             ANO_COLETA<="2020") %>% 
                  group_by(CODIGO),
                aes(CODIGO,
                    oxigenio_dissolvido))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=2,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=2,
             ymax=4,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=4,
             ymax=5,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=6,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=6,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
   geom_boxplot(
     # aes(
     #   x = oxigenio_dissolvido,
     #   ymin = min(oxigenio_dissolvido),
     #   lower = quantile(oxigenio_dissolvido, 0.30, na.rm = TRUE),
     #   middle = median(oxigenio_dissolvido),
     #   upper = quantile(oxigenio_dissolvido, 0.80, na.rm = TRUE),
     #   ymax = max(oxigenio_dissolvido)
     # ),
     # stat = "identity",
     fill='#F8F8FF',
     color="black",
     outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
     width= 0.7
   )+
   labs(title = "Oxigênio Dissolvido no período 2010-2020",
        x=NULL,
        y=NULL)+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(
       expand = expansion(mult = c(0,0)),
       n.breaks = 11,
       limits = c(-1,21))+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```

```{r Gráfico OD 3 periodos juntos, echo = TRUE, warning=FALSE, message = FALSE, fig.cap="Oxigênio Dissolvido no período 1990-2020"}
grid.arrange(od_p1, od_p2, od_p3, ncol = 3)
```

```{r Salvando OD, warning=FALSE, message = FALSE,}
ggsave("od.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = od,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_p1.png",
       plot = od_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_p2.png",
       plot = od_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_p3.png",
       plot = od_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(od_p1, od_p2, od_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

```{r Gráfico OD_chernobyl, echo = FALSE, warning=FALSE, message = FALSE}
# p1 <- function(plan_wide_19902020, ANO_COLETA) {
#   plan_wide_19902020 %>% 
#     filter(ANO_COLETA > "1990" &
#            ANO_COLETA <= "2000")
# }
# 
# 
# classes_od <- function(plan_wide_19902020, parametro, periodo){
#   ggplot(plan_wide_19902020 %>%
#            periodo),
#   aes(CODIGO,
#       parametro)
# }


# (od_chernobyl <- ggplot(plan_wide_19902020 %>%
#                           p1(ANO_COLETA > "1990" &
#                                ANO_COLETA <= "2000"),
#                         aes(CODIGO,
#                             oxigenio_dissolvido))+
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=-Inf,
#              ymax=2,
#              alpha=1,
#              fill="#ac5079")+ #>pior classe
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=2,
#              ymax=4,
#              alpha=1,
#              fill="#eb5661")+ #classe 4
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=4,
#              ymax=5,
#              alpha=1,
#              fill="#fcf7ab")+ #classe 3
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=5,
#              ymax=6,
#              alpha=1,
#              fill="#70c18c")+ #classe 2
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=6,
#              ymax=Inf,
#              alpha=1,
#              fill="#8dcdeb")+ #classe 1
#     stat_boxplot(geom = 'errorbar',
#                  width=0.3,
#                  position = position_dodge(width = 0.65))+
#     geom_boxplot(fill='#F8F8FF',
#                  color="black",
#                  outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
#                  width= 0.7)+
#     labs(title = "Oxigênio Dissolvido no período 1990-2000",
#          x="Estação",
#          y="mg/L")+
#     # geom_jitter(width = .07,
#     #             alpha=.15,
#     #             size=1.,
#     #             color="black")+
#     ggbeeswarm::geom_quasirandom(
#       size = 1.2,
#       alpha = .25,
#       width = .07,
#     )+
#     scale_y_continuous(expand = expansion(mult = c(0,0)),
#                        n.breaks = 11,
#                        limits = c(-1,21))+
#     scale_x_discrete(limits = c("87398500",
#                                 "87398980",
#                                 "87398900",
#                                 "87398950",
#                                 "87405500",
#                                 "87406900",
#                                 "87409900"),
#                      labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
#     )+
#     geom_smooth(method = "lm",
#                 se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
#                 aes(group=1),
#                 alpha=.5,
#                 na.rm = TRUE,
#                 size = 1)+
#     # geom_line(
#     #   aes(color="red"),
#     #   alpha=.0)+
#     # scale_color_manual("Legenda",
#     #                    guide="legend",
#     #                    values = c("Classe 1"="#8dcdeb",
#     #                               "Classe 2"="#70c18c",
#     #                               "Classe 3"="#fcf7ab",
#     #                               "Classe 4"="#eb5661",
#     #                               "Pior Classe"="#ac5079"))+
#     # guides(color=guide_legend(override.aes = list(linetype=c(1,1,1,1,1),
#   #                                               lwd=c(2,2,2,2,2),
#   #                                               shape=c(NA,NA,NA,NA,NA),
#   #                                               alpha=1)))+
#   theme(
#     plot.title = element_text(size = 19),
#     axis.title.y = element_text(size = 15),
#     axis.text.y = element_text(size = 17),
#     axis.text.x = element_text(size = 17),
#   )
# )
```

```{r Gráfico IQA OD periodo1, echo = FALSE, message=FALSE, warning=FALSE}
(iqaod_p1 <-ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA > "1990" &
                                ANO_COLETA <= "2000"),
                   aes(CODIGO,
                       IQA_OD, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA para o parâmetro Oxigênio Dissolvido 1990-2000",
         x="Estação",
         y="")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```

```{r Gráfico IQA OD periodo2, echo = FALSE, warning= FALSE, message = FALSE}
(iqaod_p2 <-ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA > "2000" &
                                ANO_COLETA <= "2010"),
                   aes(CODIGO,
                       IQA_OD, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA para o parâmetro Oxigênio Dissolvido 2000-2010",
         x="Estação",
         y="")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)

```

```{r Gráfico IQA OD periodo3, echo = FALSE, warning=FALSE, message = FALSE}
(iqaod_p3 <-ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA > "2010" &
                                ANO_COLETA <= "2020"),
                   aes(CODIGO,
                       IQA_OD, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA para o parâmetro Oxigênio Dissolvido 2010-2020",
         x="Estação",
         y="")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```

```{r Gráfico OD_IQA 6 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(iqaod_p1, iqaod_p2, iqaod_p3, ncol = 3)
```

```{r Sumário OD, echo = FALSE, warning=FALSE, message = FALSE,}
(sum_od_p1 <- plan_wide_19902020 %>%
    select(CODIGO, oxigenio_dissolvido, ANO_COLETA) %>% 
    filter(ANO_COLETA>"1990" &
              ANO_COLETA<="2000") %>% 
    group_by(CODIGO) %>% 
    summarize(
       min = 
          min(oxigenio_dissolvido, na.rm = TRUE),
       q1 = 
          quantile(oxigenio_dissolvido, 0.25, na.rm = TRUE),
       median = 
          median(oxigenio_dissolvido, na.rm = TRUE),
       mean = 
          mean(oxigenio_dissolvido, na.rm= TRUE),
       q3 = 
          quantile(oxigenio_dissolvido, 0.75, na.rm = TRUE),
       max = 
          max(oxigenio_dissolvido, na.rm = TRUE),
       n = 
          length(oxigenio_dissolvido)
    ) %>% 
    pivot_longer(
       !CODIGO,
       names_to = "par",
       values_to = "valor"
    ) %>% 
    pivot_wider(names_from = CODIGO,
                values_from = valor)
)

(sum_od_p2 <- plan_wide_19902020 %>%
      select(CODIGO, oxigenio_dissolvido, ANO_COLETA) %>% 
      filter(ANO_COLETA>"2000" &
                ANO_COLETA<="2010") %>% 
      group_by(CODIGO) %>% 
      summarize(
         min = 
            min(oxigenio_dissolvido, na.rm = TRUE),
         q1 = 
            quantile(oxigenio_dissolvido, 0.25, na.rm = TRUE),
         median = 
            median(oxigenio_dissolvido, na.rm = TRUE),
         mean = 
            mean(oxigenio_dissolvido, na.rm= TRUE),
         q3 = 
            quantile(oxigenio_dissolvido, 0.75, na.rm = TRUE),
         max = 
            max(oxigenio_dissolvido, na.rm = TRUE)
      )
)

(sum_od_p3 <- plan_wide_19902020 %>%
      select(CODIGO, oxigenio_dissolvido, ANO_COLETA) %>% 
      filter(ANO_COLETA>"2010" &
                ANO_COLETA<="2020") %>% 
      group_by(CODIGO) %>% 
      summarize(
         min = 
            min(oxigenio_dissolvido, na.rm = TRUE),
         q1 = 
            quantile(oxigenio_dissolvido, 0.25, na.rm = TRUE),
         median = 
            median(oxigenio_dissolvido, na.rm = TRUE),
         mean = 
            mean(oxigenio_dissolvido, na.rm= TRUE),
         q3 = 
            quantile(oxigenio_dissolvido, 0.75, na.rm = TRUE),
         max = 
            max(oxigenio_dissolvido, na.rm = TRUE)
      )
)

#   pivot_wider(id_cols = CODIGO,
#               names_from = CODIGO,
#               values_from = oxigenio_dissolvido)
# 
# 
#   group_by(CODIGO) %>%
#   get_summary_stats(type = "common") %>%
#   pivot_wider(id_cols = variable,
#               names_from = CODIGO,
#               values_from = variable$oxigenio_dissolvido)
# 
# # install.packages("ggpubr")
# # library(ggpubr)
```


### Demanda Bioquímica de Oxigênio

```{r Gráfico DBO facetted, fig.cap="Demanda Bioquímica de Oxigênio no período 1990-2020"}
(dbo <- ggplot(plan_wide_19902020,
               aes(x = CODIGO,
                   y = DBO))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=10,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=5,
            ymax=10,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3,
            ymax=5,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Demanda Bioquímica de Oxigênio no período 1990-2020",
        x="Estação",
        y="mg/L")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                      n.breaks = 8,
                      limits = c(1,100),
                      trans = "log10")+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico DBO período1, echo = FALSE, warning = FALSE, message = FALSE}
(dbo_p1<-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"1990" &
                             ANO_COLETA<="2000"),
                aes(CODIGO,
                    DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=10,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=10,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3,
             ymax=5,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=3,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Demanda Bioquímica de Oxigênio no período 1990-2000",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(1,100),
                       trans = "log10")+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico DBO período2, echo = FALSE, warning = FALSE, message = FALSE}
(dbo_p2<-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2000" &
                             ANO_COLETA<="2010"),
                aes(CODIGO,
                    DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=10,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=10,
             alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3,
            ymax=5,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Demanda Bioquímica de Oxigênio no período 2000-2010",
        x="Estação",
        y="mg/L")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(1,100),
                       trans = "log10")+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico DBO período3, echo = FALSE, warning = FALSE, message = FALSE}
(dbo_p3<-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2010" &
                             ANO_COLETA<="2020"),
                aes(CODIGO,
                    DBO, na.rm=TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=10,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=10,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3,
             ymax=5,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=3,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Demanda Bioquímica de Oxigênio no período 2010-2020",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(1,100),
                       trans = "log10")+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
        geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico IQA DBO periodo1, echo = FALSE, warning = FALSE, message = FALSE}
(iqa_dbo1<-ggplot(plan_wide_19902020 %>% 
                    filter(ANO_COLETA>"1990" &
                             ANO_COLETA<="2000"),
                  aes(CODIGO,
                      IQA_DBO))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=19,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=19,
            ymax=36,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=36,
            ymax=51,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=51,
            ymax=79,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=79,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1))
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Variação do IQA para o parâmetro DBO 1990-2020",
        x="Estação",
        y="mg/L")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico IQA DBO periodo2, echo = FALSE, warning = FALSE, message = FALSE}
(iqa_dbo2<-ggplot(plan_wide_19902020%>% 
                     filter(ANO_COLETA>"2000" &
                               ANO_COLETA<="2010"),
                  aes(CODIGO,
                      IQA_DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1))
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Variação do IQA para o parâmetro DBO 2000-2010",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico IQA DBO periodo3, echo = FALSE, warning = FALSE, message = FALSE}
(iqa_dbo3<-ggplot(plan_wide_19902020%>% 
                     filter(ANO_COLETA>"2010" &
                               ANO_COLETA<="2020"),
                  aes(CODIGO,
                      IQA_DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1))
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Variação do IQA para o parâmetro DBO 2010-2020",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
        geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico DBO 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3)
```

```{r Sumário DBO, warning=FALSE, message = FALSE,}
(sum_dbo_p1 <- plan_wide_19902020 %>%
   select(CODIGO, DBO, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(DBO, 
           na.rm = TRUE),
     q1 = 
       quantile(DBO, 0.25, 
                na.rm = TRUE),
     median = 
       median(DBO, 
              na.rm = TRUE),
     mean = 
       mean(DBO, 
            na.rm= TRUE),
     q3 = 
       quantile(DBO, 0.75, 
                na.rm = TRUE),
     max = 
       max(DBO, 
           na.rm = TRUE))
)

(sum_dbo_p2 <- plan_wide_19902020 %>%
    select(CODIGO, DBO, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(DBO, 
            na.rm = TRUE),
      q1 = 
        quantile(DBO, 0.25, 
                 na.rm = TRUE),
      median = 
        median(DBO, 
               na.rm = TRUE),
      mean = 
        mean(DBO, 
             na.rm= TRUE),
      q3 = 
        quantile(DBO, 0.75, 
                 na.rm = TRUE),
      max = 
        max(DBO, 
            na.rm = TRUE))
)

(sum_dbo_p3 <- plan_wide_19902020 %>%
    select(CODIGO, DBO, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(DBO, 
            na.rm = TRUE),
      q1 = 
        quantile(DBO, 0.25, 
                 na.rm = TRUE),
      median = 
        median(DBO, 
               na.rm = TRUE),
      mean = 
        mean(DBO, 
             na.rm= TRUE),
      q3 = 
        quantile(DBO, 0.75, 
                 na.rm = TRUE),
      max = 
        max(DBO, 
            na.rm = TRUE))
)
```

```{r Salvando DBO, warning=FALSE, message = FALSE,}
ggsave("dbo.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = dbo,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_p1.png",
       plot = dbo_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_p2.png",
       plot = dbo_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_p3.png",
       plot = dbo_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Fósforo total

```{r Gráfico fósforo total facetted, fig.cap="Fósforo total no período 1990-2020"}
(ptot <- ggplot(plan_wide_19902020,
                aes(CODIGO,
                    fosforo_total))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0.15,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0.1,
            ymax=0.15,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=0.1,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
  facet_wrap(~periodo)+
    labs(title = "Fósforo total no período 1990-2020",
         x="Estação",
         y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
                                 max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
                      trans = "log10")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico Fósforo total periodo1, warning = FALSE, message = FALSE}
(ptot_p1<-ggplot(plan_wide_19902020%>% 
                   filter(ANO_COLETA>"1990" &
                             ANO_COLETA<="2000"),
                 aes(CODIGO,
                     fosforo_total))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.15,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.1,
             ymax=0.15,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=0.1,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Fósforo total no período 1990-2000",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
                                  max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
                       trans = "log10")+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)

```

```{r Gráfico Fósforo total periodo2, warning = FALSE, message = FALSE}
(ptot_p2 <- ggplot(plan_wide_19902020%>% 
                      filter(ANO_COLETA>"2000" &
                                ANO_COLETA<="2010"),
                   aes(CODIGO,
                       fosforo_total))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.15,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.1,
             ymax=0.15,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=0.1,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Fósforo total no período 2000-2010",
         x="Estação",
         y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
                                 max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
                      trans = "log10")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)

```

```{r Gráfico Fósforo total periodo3, warning = FALSE, message = FALSE}
(ptot_p3 <- ggplot(plan_wide_19902020%>% 
                      filter(ANO_COLETA>"2010" &
                                ANO_COLETA<="2020"),
                   aes(CODIGO,
                       fosforo_total))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.15,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.1,
             ymax=0.15,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=0.1,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Fósforo total no período 2010-2020",
         x="Estação",
         y="mg/L")+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(min(plan_wide_19902020$fosforo_total, na.rm = TRUE),
                                  max(plan_wide_19902020$fosforo_total), na.rm = TRUE),
                       trans = "log10")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)

```

```{r Gráfico Ptot 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3)
```

```{r Sumário Fósforo total, warning=FALSE, message = FALSE,}
(sum_ptot_p1 <- plan_wide_19902020 %>%
    select(CODIGO, fosforo_total, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(fosforo_total, na.rm = TRUE),
     q1 = 
       quantile(fosforo_total, 0.25, na.rm = TRUE),
     median = 
       median(fosforo_total, na.rm = TRUE),
     mean = 
       mean(fosforo_total, na.rm= TRUE),
     q3 = 
       quantile(fosforo_total, 0.75, na.rm = TRUE),
     max = 
       max(fosforo_total, na.rm = TRUE)))

(sum_ptot_p2 <- plan_wide_19902020 %>%
    select(CODIGO, fosforo_total, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(fosforo_total, na.rm = TRUE),
      q1 = 
        quantile(fosforo_total, 0.25, na.rm = TRUE),
      median = 
        median(fosforo_total, na.rm = TRUE),
      mean = 
        mean(fosforo_total, na.rm= TRUE),
      q3 = 
        quantile(fosforo_total, 0.75, na.rm = TRUE),
      max = 
        max(fosforo_total, na.rm = TRUE)))

(sum_ptot_p3 <- plan_wide_19902020 %>%
    select(CODIGO, fosforo_total, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(fosforo_total, na.rm = TRUE),
      q1 = 
        quantile(fosforo_total, 0.25, na.rm = TRUE),
      median = 
        median(fosforo_total, na.rm = TRUE),
      mean = 
        mean(fosforo_total, na.rm= TRUE),
      q3 = 
        quantile(fosforo_total, 0.75, na.rm = TRUE),
      max = 
        max(fosforo_total, na.rm = TRUE)))

```

```{r Salvando Ptot, warning=FALSE, message = FALSE,}
ggsave("ptot.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = ptot,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_p1.png",
       plot = ptot_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_p2.png",
       plot = ptot_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_p3.png",
       plot = ptot_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Escherichia coli

```{r Gráfico Ecoli facetted, fig.cap="Escherichia-coli-gravataí no período 1990-2020", warning = FALSE, message = FALSE}
ecoli__class <- function() {
  list(annotate("rect",
                xmin=-Inf,
                xmax=Inf,
                ymin=3200,
                ymax=Inf,
                alpha=1,
                fill="#ac5079")+ #>pior classe
         annotate("rect",
                  xmin=-Inf,
                  xmax=Inf,
                  ymin=800,
                  ymax=3200,
                  alpha=1,
                  fill="#fcf7ab")+ #classe 3
         annotate("rect",
                  xmin=-Inf,
                  xmax=Inf,
                  ymin=160,
                  ymax=800,
                  alpha=1,
                  fill="#70c18c")+ #classe 2
         annotate("rect",
                  xmin=-Inf,
                  xmax=Inf,
                  ymin=0,
                  ymax=160,
                  alpha=1,
                  fill="#8dcdeb") #classe 1
  )
}
  
(ecoli <- ggplot(plan_wide_19902020,
                 aes(CODIGO,
                     E_coli))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3200,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=800,
            ymax=3200,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=160,
            ymax=800,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=160,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Escherichia coli no período 1990-2020",
        x="Estação",
        y="NMP/100mL")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      # n.breaks = 9,
                      n.breaks = 6,
                      limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
                                 max(plan_wide_19902020$E_coli, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()+
    theme(
        axis.text.y = element_text(
          angle = 90, 
          # size=15,
          # face=2
        )
    )
)
```

```{r Gráfico Ecoli periodo1, warning = FALSE, message = FALSE}
(ecoli_p1 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"1990" &
                                 ANO_COLETA<="2000"),
                    aes(CODIGO,
                        E_coli))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3200,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=800,
             ymax=3200,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=160,
             ymax=800,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=160,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Escherichia coli no período 1990-2000",
         x="Estação",
         y="NMP/100mL")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
                                 max(plan_wide_19902020$E_coli, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico Ecoli periodo2, warning = FALSE, message = FALSE}
(ecoli_p2 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2000" &
                                 ANO_COLETA<="2010"),
                    aes(CODIGO,
                        E_coli))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3200,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=800,
             ymax=3200,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=160,
             ymax=800,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=160,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Escherichia coli no período 2000-2010",
         x="Estação",
         y="NMP/100mL")+
    scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                       n.breaks = 9,
                       limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
                                  max(plan_wide_19902020$E_coli, na.rm = TRUE)),
                       trans = "log10",
                       labels = scales::number_format(accuracy = 1,
                                                      decimal.mark = ",",
                                                      big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico Ecoli periodo3, warning = FALSE, message = FALSE}
(ecoli_p3 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2010" &
                                 ANO_COLETA<="2020"),
                    aes(CODIGO,
                        E_coli))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3200,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=800,
             ymax=3200,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=160,
             ymax=800,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=160,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Escherichia coli no período 2010-2020",
         x="Estação",
         y="NMP/100mL")+
    scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                       n.breaks = 9,
                       limits = c(min(plan_wide_19902020$E_coli, na.rm = TRUE),
                                  max(plan_wide_19902020$E_coli, na.rm = TRUE)),
                       trans = "log10",
                       labels = scales::number_format(accuracy = 1,
                                                      decimal.mark = ",",
                                                      big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico ecoli 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3)
```

```{r Sumário Ecoli, warning=FALSE, message = FALSE,}
(sum_ecoli_p1 <- plan_wide_19902020 %>%
    select(CODIGO, E_coli, ANO_COLETA) %>% 
    filter(ANO_COLETA>"1990" &
              ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(E_coli, 
           na.rm = TRUE),
     q1 = 
       quantile(E_coli, 0.25, 
                na.rm = TRUE),
     median = 
       median(E_coli, 
              na.rm = TRUE),
     mean = 
       mean(E_coli, 
            na.rm= TRUE),
     q3 = 
       quantile(E_coli, 0.75, 
                na.rm = TRUE),
     max = 
       max(E_coli, 
           na.rm = TRUE))
)

(sum_ecoli_p2 <- plan_wide_19902020 %>%
    select(CODIGO, E_coli, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(E_coli, 
            na.rm = TRUE),
      q1 = 
        quantile(E_coli, 0.25, 
                 na.rm = TRUE),
      median = 
        median(E_coli, 
               na.rm = TRUE),
      mean = 
        mean(E_coli, 
             na.rm= TRUE),
      q3 = 
        quantile(E_coli, 0.75, 
                 na.rm = TRUE),
      max = 
        max(E_coli, 
            na.rm = TRUE))
)

(sum_ecoli_p3 <- plan_wide_19902020 %>%
    select(CODIGO, E_coli, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(E_coli, 
            na.rm = TRUE),
      q1 = 
        quantile(E_coli, 0.25, 
                 na.rm = TRUE),
      median = 
        median(E_coli, 
               na.rm = TRUE),
      mean = 
        mean(E_coli, 
             na.rm= TRUE),
      q3 = 
        quantile(E_coli, 0.75, 
                 na.rm = TRUE),
      max = 
        max(E_coli, 
            na.rm = TRUE))
)
```

```{r Salvando ecoli, warning=FALSE, message = FALSE,}
ggsave("ecoli.png",
       plot = ecoli,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_p1.png",
       plot = ecoli_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_p2.png",
       plot = ecoli_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_p3.png",
       plot = ecoli_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Nitrogênio amoniacal

```{r Gráfico Nitrogênio total facetted, fig.cap="nitrogenio-gravataí no período 1990-2020", warning = FALSE, message = FALSE}
(namon <- ggplot(plan_wide_19902020,
                 aes(CODIGO,
                     nitro_total))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3.7,
            ymax=13.3,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3.7,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Nitrogênio amoniacal no período 1990-2020",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
                                 max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Nitrogênio total periodo1, warning = FALSE, message = FALSE}
(namon_p1 <- ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA>"1990" &
                               ANO_COLETA<="2000"),
                    aes(CODIGO,
                        nitro_total))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3.7,
             ymax=13.3,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=3.7,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
   labs(title = "Nitrogênio amoniacal no período 1990-2000",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
                                 max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Nitrogênio total periodo2, warning = FALSE, message = FALSE}
(namon_p2 <- ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA>"2000" &
                               ANO_COLETA<="2010"),
                    aes(CODIGO,
                        nitro_total))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3.7,
            ymax=13.3,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3.7,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Nitrogênio amoniacal no período 2000-2010",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
                                 max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Nitrogênio total periodo3, warning = FALSE, message = FALSE}
(namon_p3 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2010" &
                                 ANO_COLETA<="2020"),
                    aes(CODIGO,
                        nitro_total))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3.7,
            ymax=13.3,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3.7,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Nitrogênio amoniacal no período 2010-2020",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$nitro_total, na.rm = TRUE),
                                 max(plan_wide_19902020$nitro_total, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Namon 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3)
```

```{r Sumário Nitrogênio total, warning=FALSE, message = FALSE,}
(sum_namon_p1 <- plan_wide_19902020 %>%
   select(CODIGO, nitro_total, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(nitro_total, 
           na.rm = TRUE),
     q1 = 
       quantile(nitro_total, 0.25, 
                na.rm = TRUE),
     median = 
       median(nitro_total, 
              na.rm = TRUE),
     mean = 
       mean(nitro_total, 
            na.rm= TRUE),
     q3 = 
       quantile(nitro_total, 0.75, 
                na.rm = TRUE),
     max = 
       max(nitro_total, 
           na.rm = TRUE),
      n = 
       length(nitro_total)
   )
)

(sum_namon_p2 <- plan_wide_19902020 %>%
    select(CODIGO, nitro_total, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(nitro_total, 
            na.rm = TRUE),
      q1 = 
        quantile(nitro_total, 0.25, 
                 na.rm = TRUE),
      median = 
        median(nitro_total, 
               na.rm = TRUE),
      mean = 
        mean(nitro_total, 
             na.rm= TRUE),
      q3 = 
        quantile(nitro_total, 0.75, 
                 na.rm = TRUE),
      max = 
        max(nitro_total, 
            na.rm = TRUE))
)

(sum_namon_p3 <- plan_wide_19902020 %>%
    select(CODIGO, nitro_total, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(nitro_total, 
            na.rm = TRUE),
      q1 = 
        quantile(nitro_total, 0.25, 
                 na.rm = TRUE),
      median = 
        median(nitro_total, 
               na.rm = TRUE),
      mean = 
        mean(nitro_total, 
             na.rm= TRUE),
      q3 = 
        quantile(nitro_total, 0.75, 
                 na.rm = TRUE),
      max = 
        max(nitro_total, 
            na.rm = TRUE))
)
```

```{r Salvando namon, warning=FALSE, message = FALSE,}
ggsave("namon.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = namon,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_p1.png",
       plot = namon_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_p2.png",
       plot = namon_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_p3.png",
       plot = namon_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Turbidez

```{r Gráfico Turbidez facetted, fig.cap="turbidez-gravataí no período 1990-2020", warning = FALSE, message = FALSE}
(turb <- ggplot(plan_wide_19902020,
                   aes(CODIGO,
                       turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Turbidez no período 1990-2020",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.05)),
                      n.breaks = 16,
                      limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
                                 # 500
                                 max(plan_wide_19902020$turbidez, na.rm = TRUE)
                                 ),
                      # trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Turbidez line, warning = FALSE, message = FALSE}
(turb_line <- plan_wide_19902020 %>%
  filter(ANO_COLETA > "1990" &
           ANO_COLETA <= "2020") %>%
  select(CODIGO, turbidez, DATA_COLETA, periodo) %>%
  group_by(CODIGO) %>%
  ggplot(
    aes(x = DATA_COLETA,
        y = turbidez,
        color = CODIGO
    ))+
    geom_line(
      # aes(color = CODIGO),
      na.rm = TRUE)+
    geom_point(
      # aes(color = CODIGO),
      na.rm = TRUE)+
    scale_x_date(
      limits = as.Date(c(
        "1990-01-01", 
        "2021-01-01"
        # NA #pode usar NA também
      )),
      expand = c(0.0, 0.0),
      date_breaks = "10 years",
      minor_breaks = "5 years",
      date_labels = "%Y",
    )+
  # geom_smooth(
  #   # aes(color = CODIGO),
  #   method = "lm",
  #   # formula = y ~ poly(x, 2),
  #   # span = 0.2,
  #   se = TRUE, #se deixar TRUE gera o intervalo de confiança de 95%
  #   aes(group = 1),
  #   alpha =.5,
  #   na.rm = TRUE,
  #   size = 0.3,
  #   # fullrange = TRUE,
  #   # show.legend = TRUE
  # )+
  # stat_smooth(
  #   geom = "smooth",
  #   # span = 0.2,
  #   se = FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
  #   # aes(group = 1),
  #   # alpha =.5,
  #   na.rm = TRUE,
  #   # size = 0.3,
  #   fullrange = TRUE,
  #   show.legend = TRUE
  # )+
  facet_wrap(
    ~CODIGO,
    nrow = 4,
  )+
  theme_bw()
)
```


```{r Gráfico Turbidez periodo1, warning = FALSE, message = FALSE}
(turb_p1 <- ggplot(plan_wide_19902020 %>% 
                     filter(ANO_COLETA>"1990" &
                              ANO_COLETA<="2000"),
                   aes(CODIGO,
                       turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Turbidez no período 1990-2000",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
                                 max(plan_wide_19902020$turbidez, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Turbidez periodo2, warning = FALSE, message = FALSE}
(turb_p2 <- ggplot(plan_wide_19902020 %>% 
                     filter(ANO_COLETA>"2000" &
                              ANO_COLETA<="2010"),
                   aes(CODIGO,
                       turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Turbidez no período 2000-2010",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
                                 max(plan_wide_19902020$turbidez, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Turbidez periodo3, warning = FALSE, message = FALSE}
(turb_p3 <- ggplot(plan_wide_19902020 %>% 
                     filter(ANO_COLETA>"2010" &
                              ANO_COLETA<="2020"),
                   aes(CODIGO,
                       turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Turbidez no período 2010-2020",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$turbidez, na.rm = TRUE),
                                 max(plan_wide_19902020$turbidez, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico turb 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3)
```

```{r Sumário Turbidez, warning=FALSE, message = FALSE,}
(sum_turb_p1 <- plan_wide_19902020 %>%
   select(CODIGO, turbidez, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(turbidez, 
           na.rm = TRUE),
     q1 = 
       quantile(turbidez, 0.25, 
                na.rm = TRUE),
     median = 
       median(turbidez, 
              na.rm = TRUE),
     mean = 
       mean(turbidez, 
            na.rm= TRUE),
     q3 = 
       quantile(turbidez, 0.75, 
                na.rm = TRUE),
     max = 
       max(turbidez, 
           na.rm = TRUE))
)

(sum_turb_p2 <- plan_wide_19902020 %>%
    select(CODIGO, turbidez, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(turbidez, 
            na.rm = TRUE),
      q1 = 
        quantile(turbidez, 0.25, 
                 na.rm = TRUE),
      median = 
        median(turbidez, 
               na.rm = TRUE),
      mean = 
        mean(turbidez, 
             na.rm= TRUE),
      q3 = 
        quantile(turbidez, 0.75, 
                 na.rm = TRUE),
      max = 
        max(turbidez, 
            na.rm = TRUE))
)

(sum_turb_p3 <- plan_wide_19902020 %>%
    select(CODIGO, turbidez, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(turbidez, 
            na.rm = TRUE),
      q1 = 
        quantile(turbidez, 0.25, 
                 na.rm = TRUE),
      median = 
        median(turbidez, 
               na.rm = TRUE),
      mean = 
        mean(turbidez, 
             na.rm= TRUE),
      q3 = 
        quantile(turbidez, 0.75, 
                 na.rm = TRUE),
      max = 
        max(turbidez, 
            na.rm = TRUE))
) 
```

```{r Salvando turb, warning=FALSE, message = FALSE,}
ggsave("turb.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = turb,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_p1.png",
       plot = turb_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_p2.png",
       plot = turb_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_p3.png",
       plot = turb_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### pH

```{r Gráfico pH facetted, fig.cap="pH-gravataí no período 1990-2020", warning = FALSE, message = FALSE}
(pH <- ggplot(plan_wide_19902020,
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "pH no período 1990-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH periodo1, warning = FALSE, message = FALSE}
(pH_p1 <- ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"1990" &
                            ANO_COLETA<="2000"),
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "pH no período 1990-2000",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH periodo2, warning = FALSE, message = FALSE}
(pH_p2 <- ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2000" &
                            ANO_COLETA<="2010"),
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "pH no período 2000-2010",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH periodo3, warning = FALSE, message = FALSE}
(pH_p3 <- ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2010" &
                            ANO_COLETA<="2020"),
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "pH no período 2010-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3)
```

```{r Sumário pH, warning=FALSE, message = FALSE,}
(sum_pH_p1 <- plan_wide_19902020 %>%
   select(CODIGO, pH, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(pH, 
           na.rm = TRUE),
     q1 = 
       quantile(pH, 0.25, 
                na.rm = TRUE),
     median = 
       median(pH, 
              na.rm = TRUE),
     mean = 
       mean(pH, 
            na.rm= TRUE),
     q3 = 
       quantile(pH, 0.75, 
                na.rm = TRUE),
     max = 
       max(pH, 
           na.rm = TRUE))
)

(sum_pH_p2 <- plan_wide_19902020 %>%
    select(CODIGO, pH, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(pH, 
            na.rm = TRUE),
      q1 = 
        quantile(pH, 0.25, 
                 na.rm = TRUE),
      median = 
        median(pH, 
               na.rm = TRUE),
      mean = 
        mean(pH, 
             na.rm= TRUE),
      q3 = 
        quantile(pH, 0.75, 
                 na.rm = TRUE),
      max = 
        max(pH, 
            na.rm = TRUE))
) 

(sum_pH_p3 <- plan_wide_19902020 %>%
    select(CODIGO, pH, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(pH, 
            na.rm = TRUE),
      q1 = 
        quantile(pH, 0.25, 
                 na.rm = TRUE),
      median = 
        median(pH, 
               na.rm = TRUE),
      mean = 
        mean(pH, 
             na.rm= TRUE),
      q3 = 
        quantile(pH, 0.75, 
                 na.rm = TRUE),
      max = 
        max(pH, 
            na.rm = TRUE))
)
```

```{r Salvando pH, warning=FALSE, message = FALSE,}
ggsave("pH.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = pH,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_p1.png",
       plot = pH_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_p2.png",
       plot = pH_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_p3.png",
       plot = pH_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Sólidos totais

```{r Gráfico SólTot facetted, fig.cap="sólidos-totais-gravataí no período 1990-2020", warning = FALSE, message = FALSE}
(SolTot <- ggplot(plan_wide_19902020,
                  aes(CODIGO,
                      solidos_totais))+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Sólidos totais no período 1990-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico SólTot periodo1, warning = FALSE, message = FALSE}
(SolTot_p1 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"1990" &
                                ANO_COLETA<="2000"),
                     aes(CODIGO,
                         solidos_totais))+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Sólidos totais no período 1990-2000",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico SólTot periodo2, warning = FALSE, message = FALSE}
(SolTot_p2 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2000" &
                                ANO_COLETA<="2010"),
                     aes(CODIGO,
                         solidos_totais))+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Sólidos totais no período 2000-2010",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico SólTot periodo3, warning = FALSE, message = FALSE}
(SolTot_p3 <- ggplot(plan_wide_19902020 %>% 
                        filter(ANO_COLETA>"2010" &
                                  ANO_COLETA<="2020"),
                     aes(CODIGO,
                         solidos_totais))+
    annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=500,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Sólidos totais no período 2010-2020",
         x="Estação",
         y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$solidos_totais, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico SólTot 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3)
```

```{r Sumário Sólidos Totais, warning=FALSE, message = FALSE,}
(sum_SolTot_p1 <- plan_wide_19902020 %>%
   select(CODIGO, solidos_totais, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(solidos_totais, 
           na.rm = TRUE),
     q1 = 
       quantile(solidos_totais, 0.25, 
                na.rm = TRUE),
     median = 
       median(solidos_totais, 
              na.rm = TRUE),
     mean = 
       mean(solidos_totais, 
            na.rm= TRUE),
     q3 = 
       quantile(solidos_totais, 0.75, 
                na.rm = TRUE),
     max = 
       max(solidos_totais, 
           na.rm = TRUE))
)

(sum_SolTot_p2 <- plan_wide_19902020 %>%
    select(CODIGO, solidos_totais, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(solidos_totais, 
            na.rm = TRUE),
      q1 = 
        quantile(solidos_totais, 0.25, 
                 na.rm = TRUE),
      median = 
        median(solidos_totais, 
               na.rm = TRUE),
      mean = 
        mean(solidos_totais, 
             na.rm= TRUE),
      q3 = 
        quantile(solidos_totais, 0.75, 
                 na.rm = TRUE),
      max = 
        max(solidos_totais, 
            na.rm = TRUE))
)

(sum_SolTot_p3 <- plan_wide_19902020 %>%
    select(CODIGO, solidos_totais, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(solidos_totais, 
            na.rm = TRUE),
      q1 = 
        quantile(solidos_totais, 0.25, 
                 na.rm = TRUE),
      median = 
        median(solidos_totais, 
               na.rm = TRUE),
      mean = 
        mean(solidos_totais, 
             na.rm= TRUE),
      q3 = 
        quantile(solidos_totais, 0.75, 
                 na.rm = TRUE),
      max = 
        max(solidos_totais, 
            na.rm = TRUE))
)
```

```{r Salvando SolTot, warning=FALSE, message = FALSE,}
ggsave("SolTot.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = SolTot,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_p1.png",
       plot = SolTot_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_p2.png",
       plot = SolTot_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_p3.png",
       plot = SolTot_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### IQA

```{r Gráfico IQA facetted, fig.cap="iqa-gravataí no período 1990-2020", echo = FALSE, message=FALSE, warning=FALSE}
(iqa <-ggplot(plan_wide_19902020,
              aes(CODIGO,
                  IQA, na.rm = TRUE))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=25,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=25,
            ymax=50,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=50,
            ymax=70,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=70,
            ymax=90,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=90,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7,
                na.rm = TRUE)+
   facet_wrap(~periodo)+
   labs(title = "Variação do IQA no período 1990-2020",
        x="Estação",
        y="IQA")+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
   # theme(axis.title.y = element_blank())
)
```

```{r Gráfico IQA periodo1, echo = FALSE, message=FALSE, warning=FALSE}
(iqa_p1 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA > "1990" &
                            ANO_COLETA <= "2000"),
                 aes(CODIGO,
                     IQA, na.rm = TRUE))+
    annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=25,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=25,
            ymax=50,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=50,
            ymax=70,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=70,
            ymax=90,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=90,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA no período 1990-2000",
         x="Estação",
         y="")+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
   theme_grafs()+
   theme(axis.title.y = element_blank())
)
```

```{r Gráfico IQA periodo2, echo = FALSE, message=FALSE, warning=FALSE}
(iqa_p2 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA > "2000" &
                            ANO_COLETA <= "2010"),
                 aes(CODIGO,
                     IQA, na.rm = TRUE))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=25,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=25,
            ymax=50,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=50,
            ymax=70,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=70,
            ymax=90,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=90,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7,
                na.rm = TRUE)+
   labs(title = "Variação do IQA no período 2000-2010",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
 theme_grafs()+
   theme(axis.title.y = element_blank()
   )
)
```

```{r Gráfico IQA periodo3, echo = FALSE, message=FALSE, warning=FALSE}
(iqa_p3 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA > "2010" &
                            ANO_COLETA <= "2020"),
                 aes(CODIGO,
                     IQA, na.rm = TRUE))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=25,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=25,
            ymax=50,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=50,
            ymax=70,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=70,
            ymax=90,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=90,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7,
                na.rm = TRUE)+
   labs(title = "Variação do IQA no período 2010-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
    theme_grafs()+
    theme(axis.title.y = element_blank())
)
```

```{r Gráfico IQA 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3)
```

```{r Sumário IQA, warning=FALSE, message = FALSE,}
(sum_IQA_p1 <- plan_wide_19902020 %>%
   select(CODIGO, IQA, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(IQA, 
           na.rm = TRUE),
     q1 = 
       quantile(IQA, 0.25, 
                na.rm = TRUE),
     median = 
       median(IQA, 
              na.rm = TRUE),
     mean = 
       mean(IQA, 
            na.rm= TRUE),
     q3 = 
       quantile(IQA, 0.75, 
                na.rm = TRUE),
     max = 
       max(IQA, 
           na.rm = TRUE),
     n = 
        length(IQA)
   )
)

(sum_IQA_p2 <- plan_wide_19902020 %>%
    select(CODIGO, IQA, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(IQA, 
            na.rm = TRUE),
      q1 = 
        quantile(IQA, 0.25, 
                 na.rm = TRUE),
      median = 
        median(IQA, 
               na.rm = TRUE),
      mean = 
        mean(IQA, 
             na.rm= TRUE),
      q3 = 
        quantile(IQA, 0.75, 
                 na.rm = TRUE),
      max = 
        max(IQA, 
            na.rm = TRUE),
      n = 
        length(IQA)
      )
)

(sum_IQA_p3 <- plan_wide_19902020 %>%
    select(CODIGO, IQA, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>%
    # ?as_factor(CODIGO) %>% 
    group_by(CODIGO) %>%
    summarize(
      min = 
        min(IQA, 
            na.rm = TRUE),
      q1 = 
        quantile(IQA, 0.25, 
                 na.rm = TRUE),
      median = 
        median(IQA, 
               na.rm = TRUE),
      mean = 
        mean(IQA, 
             na.rm= TRUE),
      q3 = 
        quantile(IQA, 0.75, 
                 na.rm = TRUE),
      max = 
        max(IQA, 
            na.rm = TRUE),
      n = 
        length(IQA),
      NAs = 
        sum(is.na(IQA))
      ) %>% 
  mutate(
    "%NA" = NAs/n*100
  )
)

```

```{r Salvando iqa, warning=FALSE, message = FALSE,}
ggsave("iqa.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = iqa,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_p1.png",
       plot = iqa_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_p2.png",
       plot = iqa_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_p3.png",
       plot = iqa_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

## Testando coisas

```{r Testando coisas, include = FALSE, warning=FALSE, message = FALSE,}
# plan_wide_19902020 %>% 
#    select(CODIGO, oxigenio_dissolvido, ANO_COLETA) %>% 
#    ggplot(aes(ANO_COLETA, oxigenio_dissolvido, 
#       col = CODIGO))+
#    geom_line()+
#    facet_wrap(~ CODIGO, ncol = 7)

# df111 <- data.frame(x = c(1:100))
# glimpse(df111)
# df111$y <- 2 + 3 * df111$x + rnorm(100, sd = 40)
# 
# lm_eqn <- function(df111){
#     m <- lm(y ~ x, df111);
#     eq <- substitute(y == a + b %.% x*","~~r^2~"="~r2,
#          list(a = format(unname(coef(m)[1]), digits = 2),
#               b = format(unname(coef(m)[2]), digits = 2),
#              r2 = format(summary(m)$r.squared, digits = 3)))
#     as.character(as.expression(eq));
# } 
# p2 <- p111 +
#   geom_text(x = 25, y = 300,
#             label = lm_eqn(df111),
#             parse = TRUE)
# p2
# 
# 
# lm_eqc <- function(plan_wide_19902020){
#    m <- lm(oxigenio_dissolvido ~ CODIGO, plan_wide_19902020);
#    eq <- substitute(y == a + b %.% x*","~~r^2~"="~r2,
#                     list(a = format(unname(coef(m)[1]), digits = 2),
#                          b = format(unname(coef(m)[2]), digits = 2),
#                          r2 = format(summary(m)$r.squared, digits = 3)))
#    as.character(as.expression(eq));
# }
# 
# (od_p1 <-ggplot(plan_wide_19902020 %>%
#                    filter(ANO_COLETA>"1990" &
#                              ANO_COLETA<="2000"),
#                 aes(CODIGO,
#                     oxigenio_dissolvido))+
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=-Inf,
#                ymax=2,
#                alpha=1,
#                fill="#ac5079")+ #>pior classe
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=2,
#                ymax=4,
#                alpha=1,
#                fill="#eb5661")+ #classe 4
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=4,
#                ymax=5,
#                alpha=1,
#                fill="#fcf7ab")+ #classe 3
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=5,
#                ymax=6,
#                alpha=1,
#                fill="#70c18c")+ #classe 2
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=6,
#                ymax=Inf,
#                alpha=1,
#                fill="#8dcdeb")+ #classe 1
#       stat_boxplot(geom = 'errorbar',
#                    width=0.3,
#                    position = position_dodge(width = 0.65))+
#       geom_boxplot(fill='#F8F8FF',
#                    color="black",
#                    outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
#                    width= 0.7)+
#       labs(title = "Oxigênio Dissolvido no período 1990-2000",
#            x="Estação",
#            y="mg/L")+
#       # geom_jitter(width = .05,
#       #             alpha=.2,
#       #             size=1.5,
#       #             color="black")+
#       scale_y_continuous(expand = expansion(mult = c(0,0)),
#                          n.breaks = 11,
#                          limits = c(-1,21))+
#       scale_x_discrete(limits = c("87398500", "87398980", "87398900", "87398950", "87405500", "87406900", "87409900"))+
#       geom_smooth(method = "lm",
#                   se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
#                   aes(group=1),
#                   alpha=.5,
#                   na.rm = TRUE,
#                   size = 1)+
#       # annotate(geom_text(aes(x = "87405500", y = 15),
#       #                    label = lm_eqc(plan_wide_19902020),
#       #                    parse = TRUE,
#       #                    inherit.aes = TRUE,
#       #                    check_overlap = TRUE))+
#       #  geom_line(
#       #     aes(color="red"),
#       #     alpha=.0,
#       # )+
#       # scale_color_manual("Legenda",
#       #                    guide="legend",
#       #                    values = c("Classe 1"="#8dcdeb",
#       #                               "Classe 2"="#70c18c",
#       #                               "Classe 3"="#fcf7ab",
#       #                               "Classe 4"="#eb5661",
#       #                               "Pior Classe"="#ac5079"))+
#    # guides(color=guide_legend(override.aes = list(linetype=c(1,1,1,1,1),
#    #                                               lwd=c(2,2,2,2,2),
#    #                                               shape=c(NA,NA,NA,NA,NA),
#    #                                               alpha=1)))+
#       theme(legend.position = "bottom")+
#       theme_classic())

# list1111 <- sessionInfo()
# list1111$loadedOnly

# install.packages("ggpmisc")
# library(ggpmisc)

# summary(lm(plan_wide_19902020$CODIGO~plan_wide_19902020$DBO))
# 
# 
# p <- ggplot(data, aes(y=number, x=pod)) +
#   geom_boxplot()
# print(p)

# install.packages("GGally")


# fit = lm(plan_wide_19902020$oxigenio_dissolvido~ plan_wide_19902020$CODIGO)
# summary(fit)
# summary.lm(fit)
# 
# pacman::p_load(esquisse)

# sumario <- function(x, y){
#   x %>% 
#     group_by(CODIGO) %>%
#     summarise(
#       list(min= ~min(y, na.rm = TRUE), 
#            Q1= ~quantile(y, probs = 0.25),
#            median= ~median(y, na.rm = TRUE), 
#            Q3= ~quantile(y, probs = 0.75),
#            max= ~max(y, na.rm = TRUE)),
#       .groups = "drop"
#       )
# }
```

### Correlação

```{r Correlação, fig.cap="correlação-parametros-qualidade-agua-gravataí no período 1990-2020", time_it = TRUE, warning=FALSE, message = FALSE,}
parametros_IQA %>% 
  select(-CODIGO, -nitro_total) %>% 
  rename(
    CE = Condutividade,
    OD = oxigenio_dissolvido,
    ST = solidos_totais,
    Turb = turbidez,
    Temp = temp_agua,
    Ptot = fosforo_total,
    NAmon = nitro_amon,
    NTK = nitro_kjeldahl
  ) %>% 
  ggcorr(
    method = "complete.obs",
    # "pearson",
    # "pairwise",
    name = "Correlação",
    label = TRUE,
    label_alpha = TRUE,
    digits = 3,
    low = "#3B9AB2",
    mid = "#EEEEEE",
    high = "#F21A00",
    # palette = "RdYlBu",
    layout.exp = 0,
    legend.position = "left",
    label_round = 3,
    # legend.size = 18,
    geom = "tile",
    nbreaks = 10,
  )+
  labs(title = "Correlação entre parâmetros físico-químicos na\nBacia Hidrográfica do rio Gravataí no período 1990-2020")+
  theme_linedraw()+
  theme(
    legend.position = c(0.15, 0.6),
    legend.title = element_text(size = 16),
    legend.text = element_text(size = 14),
    # legend.spacing = unit(element_text(),
                          # units = 5)
    plot.title = element_text(hjust = 0.5,
                              size = 16)
  )

# Gráfico das correlações entre todos os parâmetros com significância
correl_IQA <- parametros_IQA %>%
  select(-CODIGO) %>%
  ggpairs(title = "Correlação entre parâmetros que compõem o IQA",
          axisLabels = "show")
```

### Condutividade elétrica
```{r Gráfico cond_elet facetted, fig.cap="condutividade-eletrica-gravataí no período 1990-2020", warning = FALSE, message = FALSE}
(cond_elet <- ggplot(plan_wide_19902020,
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
      labs(title = "Condutividade elétrica no período 1990-2020",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet periodo1, warning = FALSE, message = FALSE}
(cond_elet_p1 <- ggplot(plan_wide_19902020 %>% 
                          filter(ANO_COLETA>"2000" &
                                   ANO_COLETA<="2010"),
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
      labs(title = "Condutividade elétrica no período 1990-2000",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet periodo2, warning = FALSE, message = FALSE}
(cond_elet_p2 <- ggplot(plan_wide_19902020 %>% 
                          filter(ANO_COLETA>"2000" &
                                   ANO_COLETA<="2010"),
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Condutividade elétrica no período 2000-2010",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet periodo3, warning = FALSE, message = FALSE}
(cond_elet_p3 <- ggplot(plan_wide_19902020 %>% 
                          filter(ANO_COLETA>"2010" &
                                   ANO_COLETA<="2020"),
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Condutividade elétrica no período 2010-2020",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3)
```

```{r Sumário cond_elet, warning=FALSE, message = FALSE}
(sum_cond_elet_p1 <- plan_wide_19902020 %>%
   select(CODIGO, Condutividade, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(Condutividade, 
           na.rm = TRUE),
     q1 = 
       quantile(Condutividade, 0.25, 
                na.rm = TRUE),
     median = 
       median(Condutividade, 
              na.rm = TRUE),
     mean = 
       mean(Condutividade, 
            na.rm= TRUE),
     q3 = 
       quantile(Condutividade, 0.75, 
                na.rm = TRUE),
     max = 
       max(Condutividade, 
           na.rm = TRUE))
)

(sum_cond_elet_p2 <- plan_wide_19902020 %>%
    select(CODIGO, Condutividade, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(Condutividade, 
            na.rm = TRUE),
      q1 = 
        quantile(Condutividade, 0.25, 
                 na.rm = TRUE),
      median = 
        median(Condutividade, 
               na.rm = TRUE),
      mean = 
        mean(Condutividade, 
             na.rm= TRUE),
      q3 = 
        quantile(Condutividade, 0.75, 
                 na.rm = TRUE),
      max = 
        max(Condutividade, 
            na.rm = TRUE))
)

(sum_cond_elet_p3 <- plan_wide_19902020 %>%
    select(CODIGO, Condutividade, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(Condutividade, 
            na.rm = TRUE),
      q1 = 
        quantile(Condutividade, 0.25, 
                 na.rm = TRUE),
      median = 
        median(Condutividade, 
               na.rm = TRUE),
      mean = 
        mean(Condutividade, 
             na.rm= TRUE),
      q3 = 
        quantile(Condutividade, 0.75, 
                 na.rm = TRUE),
      max = 
        max(Condutividade, 
            na.rm = TRUE),
      n = 
        length(Condutividade))
)

# plan_wide_19902020 %>% 
#    select(CODIGO, IQA) %>% 
#    group_by(CODIGO) %>% 
#    summarize(
#       min = 
#          min(IQA, 
#              na.rm = TRUE),
#       q1 = 
#          quantile(IQA, 0.25, 
#                   na.rm = TRUE),
#       median = 
#          median(IQA, 
#                 na.rm = TRUE),
#       mean = 
#          mean(IQA, 
#               na.rm= TRUE),
#       q3 = 
#          quantile(IQA, 0.75, 
#                   na.rm = TRUE),
#       max = 
#          max(IQA, 
#              na.rm = TRUE))
```

```{r Salvando cond_elet, warning=FALSE, message = FALSE}
ggsave("cond_elet.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = cond_elet,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_p1.png",
       plot = cond_elet_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_p2.png",
       plot = cond_elet_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_p3.png",
       plot = cond_elet_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")

```
